@inproceedings{AhLiWeDe12-01,
abstract = {This paper presents an automatic system for analyzing and labeling architectural floor plans. In order to detect the locations of the rooms, the proposed systems extracts both, structural and semantic information from given floor plans. Furthermore, OCR is applied on the text layer to retrieve the meaningful room labeling. Finally, a novel post-processing is proposed to split rooms into several sub-regions if several semantic rooms share the same physical room. Our fully automatic system is evaluated on a publicly available dataset of architectural floor plans. In our experiments, we could clearly outperform other state-of-the-art approaches for room detection.},
author = {Ahmed, Sheraz and Liwicki, Marcus and Weber, Markus and Dengel, Andreas},
booktitle = {10th IAPR International Workshop on Document Analysis Systems DAS2012},
doi = {10.1109/DAS.2012.22},
file = {::},
isbn = {9780769546612},
keywords = {architec,architecture,finally,floor plan analysis,outlook future,paper gives,room detection,section iv,section v concludes,structure analysis,symbol spotting,ture,wall detection,work},
pages = {339--343},
publisher = {IEEE Computer Society},
title = {{Automatic Room Detection and Room Labeling from Architectural Floor Plans}},
year = {2012}
}

@article{LiGrBu12-01,
author = {Liwicki, M and Graves, A and Bunke, H},
journal = {Computational Intelligence Paradigms in Advanced Pattern Classification},
pages = {5--24},
publisher = {Springer Berlin/Heidelberg},
title = {{Neural Networks for Handwriting Recognition}},
year = {2012}
}
@inproceedings{LiAkUcIwOmKi11-01,
author = {Liwicki, M and Akira, Y and Uchida, S and Iwamura, M and Omachi, S and Kise, K},
booktitle = {Document Analysis and Recognition (ICDAR), 2011 International Conference on},
organization = {IEEE},
pages = {1384--1388},
title = {{Reliable Online Stroke Recovery from Offline Data with the Data-Embedding Pen}},
year = {2011}
}
@inproceedings{SoUcLi11-01,
author = {Song, W and Uchida, S and Liwicki, M},
booktitle = {Document Analysis and Recognition (ICDAR), 2011 International Conference on},
organization = {IEEE},
pages = {814--818},
title = {{Comparative Study of Part-Based Handwritten Character Recognition Methods}},
year = {2011}
}
@inproceedings{LiMaHeChBeStBlFo11-01,
author = {Liwicki, M and Malik, M I and Heuvel, C and Chen, X and Berger, C and Stoel, R and Blumenstein, M and Found, B},
booktitle = {Document Analysis and Recognition (ICDAR), 2011 International Conference on},
organization = {IEEE},
pages = {1480--1484},
title = {{Signature Verification Competition for Online and Offline Skilled Forgeries (SigComp2011)}},
year = {2011}
}
@inproceedings{SoUcLi11-02,
author = {Song, W and Uchida, S and Liwicki, M},
booktitle = {Document Analysis and Recognition (ICDAR), 2011 International Conference on},
organization = {IEEE},
pages = {784--788},
title = {{Look Inside the World of Parts of Handwritten Characters}},
year = {2011}
}
@inproceedings{WeLiSchSchStDe11-01,
abstract = {This paper proposes a new approach for drawing mode detection in online handwriting. The system classifies groups of ink traces into several categories. The main contributions of this work are as follows. First, we improve and optimize several state-of-the-art recognizers by adding new features and applying feature selections. Second, we use several classifiers for the recognition. Third, we perform multiple classifier combination strategies for combining the outputs. Finally, a large experimental evaluation on two data sets is performed: the publicly available Touch \& Write database which has been acquired on a pen-enabled multi-touch surface; and the publicly available IAMonDo-database which serves as a benchmark. In our experiments on the IAM-OnDo-database we achieved a recognition rate of 97 \%, which is much higher than other results reported in the literature. On the more balanced multi-touch surface data set we achieved a recognition rate of close to 98 \%.},
author = {Weber, Markus and Liwicki, Marcus and Schelske, Yannik T H and Schoelzel, Christopher and Strau\ss, Florian and Dengel, Andreas},
booktitle = {Proc. 11th International Conference on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Weber et al/2011/Proc. 11th International Conference on Document Analysis and Recognition/2011 - Weber et al. - MCS for Online Mode Detection Evaluation on Pen-Enabled Multi-Touch Interfaces.pdf:pdf},
keywords = {-online mode detection,multiple classifier combination,multitouch,touch,write},
pages = {957--961},
publisher = {IEEE},
title = {{MCS for Online Mode Detection : Evaluation on Pen-Enabled Multi-Touch Interfaces}},
year = {2011}
}
@inproceedings{AhWeLiDe11-01,
abstract = {In this paper, we propose an improved method for text/graphics segmentation. Text/graphics separation is a crucial preprocessing step in document analysis before further analysis and recognition can be applied. Our proposed system extends the method of Tombre et al. with a number of improvements to make it more suitable for architectural floor plans. A crucial novel preprocessing step is the detection and removal of walls before the actual segmentation. Furthermore, text components are then extracted by analyzing connected components and even considering text overlapping with graphics. Finally, a smearing approach is used to remove noise and extract the final text components. Evaluation results over the series of 90 floor plans which has also been used in reference work shows that our method has a recall of almost 99\% and a precision greater then 97\%.},
author = {Ahmed, Sheraz and Weber, Markus and Liwicki, Marcus and Dengel, Andreas and Group, Knowledge-based Systems},
booktitle = {11th International Conference on Document Analysis and Recognition},
doi = {10.1109/ICDAR.2011.153},
keywords = {-text,architectural floor plans,drawings,e,floor plan analysis,generate a semantic representation,graphics segmentation,i,of the rooms including,on the recognition of,system is to,the final aim of,the floor plan recognition},
pages = {734--738},
publisher = {IEEE},
title = {{Text/Graphics Segmentation in Architectural Floor Plans}},
year = {2011}
}
@article{AhLiWeDe11-02,
abstract = {This paper proposes a novel complete system for automated floor plan analysis. Besides applying and improv- ing state-of-the-art processing methods, we introduce novel preprocessing methods, e.g., the differentiation between thick, medium, and thin lines and the removal of components outside the convex hull of the outer walls. Especially the latter method increases the performance of the final system. In our experiments on a reference data set we compare our approach to other approaches available in the literature. We show that our system outperforms previous systems. The final room recognition accuracy is 79\%that is 10\%higher than the 69\% achieved by a state-of-the-art approach from the literature.},
author = {Ahmed, Sheraz and Liwicki, Marcus and Weber, Markus and Dengel, Andreas and Group, Knowledge-based Systems},
doi = {10.1109/ICDAR.2011.177},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Ahmed et al/2011/11th International Conference on Document Analysis and Recognition/2011 - Ahmed et al. - Improved Automatic Analysis of Architectural Floor Plans.pdf:pdf},
journal = {11th International Conference on Document Analysis and Recognition},
keywords = {architec-,floor plan analysis,room detection,structure analysis,symbol spotting,ture,wall detection},
pages = {864 -- 869},
title = {{Improved Automatic Analysis of Architectural Floor Plans}},
year = {2011}
}
@inproceedings{MaLiDe11-01,
abstract = {In this paper we evaluate the impact of two state of- the-art offline signature verification systems which are based on local and global features, respectively. It is important to take into account the real world needs of Forensic Handwriting Examiners (FHEs). In forensic scenarios, the FHEs have to make decisions not only about forged and genuine signatures but also about disguised signatures, i.e., signatures where the authentic author deliberately tries to hide his/her identity with the purpose of denial at a later stage. The disguised signatures play an important role in real forensic cases but are usually neglected in recent literature. This is the novelty of our study and the topic of this paper, i.e., investigating the performance of automated systems on disguised signatures. Two robust offline signature verification systems are slightly improved and evaluated on publicly available data sets from previous signature verification competitions. The ICDAR 2009 offline signature verification competition dataset and the ICFHR 2010 4NSigComp signatures dataset. In our experiments we observed that global features are capable of providing good results if only a detection of genuine and forged signatures is needed. Local features, however, are much better suited to solve the forensic signature verification cases when disguised signatures are also involved. Noteworthy, the system based on local features could outperform all other participants at the ICFHR 4NSigComp 2010.},
author = {Malik, Muhammad Imran and Liwicki, Marcus and Dengel, Andreas},
booktitle = {Online},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Malik, Liwicki, Dengel/2011/Online/2011 - Malik, Liwicki, Dengel - Evaluation of Local and Global Features for Offline Signature Verification.pdf:pdf},
keywords = {-signature verification,disguised signatures,forensic handwriting analysis,forgeries,mixture models},
pages = {26--30},
publisher = {CEUR},
title = {{Evaluation of Local and Global Features for Offline Signature Verification}},
year = {2011}
}
@inproceedings{LeEbDe11-01,
abstract = {In this paper we discuss recent development of handwriting recognition (HWR). In particular, the transition from pure handwrit- ing recognition to understanding of the handwritten notes is described. Therefore we first summarize the state-of-the-art in HWR. Next, two recent approaches in order to improve HWR and extracting knowledge are described. Experimental results on various data are reported and an outlook to future directions is given.},
author = {Liwicki, Marcus and Ebert, Sebastian and Dengel, Andreas},
booktitle = {Proc. 15th Int’l Conference on Knowledge-Based and Intelligent Information \& Engineering Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Ebert, Dengel/2011/Proc. 15th Int’l Conference on Knowledge-Based and Intelligent Information \& Engineering Systems/2011 - Liwicki, Ebert, Dengel - From Handwriting Recognition to Ontologie-Based I.pdf:pdf},
keywords = {edge management,handwriting recognition,information extraction,knowl-,obie,personal information model},
pages = {222--231},
publisher = {Springer-Verlag},
title = {{From Handwriting Recognition to Ontologie-Based Information Extraction of Handwritten Notes}},
year = {2011}
}
@inproceedings{LiThKaDe11-01,
abstract = {This paper proposes a novel system which automatically extracts the intended items to buy from a hand written shopping list. This intelligent shopping list relies on an ontology of the products which is provided by the shopping mall. In our scenario the shopping list is written on digital Anoto paper. After transmitting the hand written strokes to the computer, the list items are recognized by a hand writing recognition system. Next, the recognized text is parsed in order to detect the amount and the desired item. This is then matched to the underlying ontology and the intended order is recognized. Our current prototype works on an ontology of 300 products. In our real-world experiments we asked 20 persons to write shopping lists without any constrains.},
author = {Liwicki, Marcus and Thieme, Sandra and Kahl, Gerrit and Dengel, Andreas},
booktitle = {Proc. 15th international conference on Knowledge-based and intelligent information and engineering systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al/2011/Proc. 15th international conference on Knowledge-based and intelligent information and engineering systems/2011 - Liwicki et al. - An Intelligent Shopping List - Combining Digital Paper w.pdf:pdf},
keywords = {anoto,digital paper,information extraction,ontology},
pages = {187--194},
publisher = {Springer-Verlag},
title = {{An Intelligent Shopping List - Combining Digital Paper with Product Ontologies}},
year = {2011}
}
@inproceedings{WeLaRoLiDePe11-01,
abstract = {In this paper we present a method for a graph-based retrieval and its application in architectural floor plan retrieval. The proposed method is an extension of a well-known method for subgraph matching. This extension significantly reduces the storage amount and indexing time for graphs where the nodes are labeled with a rather small amount of different classes. In order to reduce the number of possible permutations, a weight function for labeled graphs is introduced and a well-founded total order is defined on the weights of the labels. Inversions which violate the order are not allowed. A computational complexity analysis of the new preprocessing is given and its completeness is proven. Furthermore, in a number of practical experiments with randomly generated graphs the improvement of the new approach is shown. In experiments performed on random sample graphs, the number of permutations has been decreased to a fraction of 10 18 in average compared to the original approach by Messmer. This makes indexing of larger graphs feasible, allowing for fast detection of subgraphs.},
author = {Weber, Markus and Langenhan, Christoph and Roth-Berghofer, Thomas and Liwicki, Marcus and Dengel, Andreas and Petzold, Frank},
booktitle = {CaseBased Reasoning Research and Development},
editor = {Ram, Ashwin and Wiratunga, Nirmalie},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Weber et al/2011/CaseBased Reasoning Research and Development/2011 - Weber et al. - Fast Subgraph Isomorphism Detection for Graph-Based Retrieval.pdf:pdf},
pages = {319--333},
publisher = {Springer Verlag, Berlin Heidelberg},
title = {{Fast Subgraph Isomorphism Detection for Graph-Based Retrieval}},
year = {2011}
}
@inproceedings{WeLiDe11-02,
abstract = {In this paper an extension of index-based subgraph matching is proposed. This extension significantly reduces the storage amount and indexing time for graphs where the nodes are labeled with a rather small amount of different classes. In order to reduce the number of pos- sible permutations, a weight function for labeled graphs is introduced and a well-founded total order is defined on the weights of the labels. Inversions which violate the order are not allowed. A computational complexity analysis of the new preprocessing is given and its complete- ness is proven. Furthermore, in a number of practical experiments with randomly generated graphs the improvement of the new approach is shown. In experiments performed on random sample graphs, the num- ber of permutations has been decreased to a fraction of 10 18 in average compared to the original approach by Messmer. This makes indexing of larger graphs feasible, allowing for fast detection of subgraphs.},
author = {Weber, Markus and Liwicki, Marcus and Dengel, Andreas},
booktitle = {GraphBased Representations in Pattern Recognition},
editor = {Jiang, Xiaoyi and Ferrer, Miquel and Torsello, Andrea},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Weber, Liwicki, Dengel/2011/GraphBased Representations in Pattern Recognition/2011 - Weber, Liwicki, Dengel - Indexing with Well-Founded Total Order for Faster Subgraph Isomorphism Detection.pdf:pdf},
pages = {185--194},
publisher = {Springer},
title = {{Indexing with Well-Founded Total Order for Faster Subgraph Isomorphism Detection}},
url = {http://www.springerlink.com/index/9674886P58434107.pdf},
year = {2011}
}
@inproceedings{LaWeLiPeDe11-01,
abstract = {The paper focuses on the early stages of the design process where the architect needs assistance in finding reference projects and describes different aspects of a concept for retrieving previous design solutions with similar structural characteristics. The proposed system offers a computational approach to extracting a few characteristic and prominent features of a floor plan which are then used to generate a semantic fingerprint. We propose the use of a visual query language and a semantic structure to query and create a floor plan repository. This enables the user of the system to sketch a schematic abstraction of a floor plan and search for floor plans that are structurally similar. It is a collective effort to create a community knowledge base about past projects and the retrieval strategies of this information. We examine the use of classic mouse and keyboard and pen- and touch-enabled interaction methods to annotate and retrieve spatial situation.},
author = {Langenhan, Christoph and Weber, Markus and Liwicki, Marcus and Petzold, Frank and Dengel, Andreas},
booktitle = {CAAD Futures},
editor = {Leclercq, Pierre and Heylighen, Ann and Martin, Genevieve},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Langenhan et al/2011/CAAD Futures/2011 - Langenhan et al. - Sketch-based Methods for Researching Building Layouts through the Semantic Fingerprint of Architecture.pdf:pdf},
pages = {85--102},
publisher = {Universit\'{e} de Li\`{e}ge Press,},
title = {{Sketch-based Methods for Researching Building Layouts through the Semantic Fingerprint of Architecture}},
year = {2011}
}
@inproceedings{DeLiWe11-01,
abstract = {Multi-touch (MT) technology becomes more and more fa- mous and several frameworks have been proposed in the last decade. All of them focus on the support of touch input, gestures, and objects. Re- cently, however, a new generation of MT-tables emerged, which allows for pen-input in addition to the touch paradigm. These devices, such as the Touch \& Write Table of DFKI, consider multiple pen interaction. In this paper we propose a software development kit (SDK) which in- tegrates the basic processing of the pen input. Moreover, the Touch \& Write SDK includes handwriting recognition and geometric shape detec- tion. Using writing mode detection the SDK automatically applies the correct recognition component based on features extracted from the pen data.},
author = {Dengel, Andreas and Liwicki, Marcus and Weber, Markus},
booktitle = {Proc. 3rd Malaysian Joint Conference on Artificial Intelligence},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Dengel, Liwicki, Weber/2011/Proc. 3rd Malaysian Joint Conference on Artificial Intelligence/2011 - Dengel, Liwicki, Weber - Touch \& Write — Penabled Collaborative Intelligence —.pdf:pdf},
keywords = {sdk,sketch-based,software architecture,touch \& write},
pages = {10 pages},
title = {{Touch \& Write — Penabled Collaborative Intelligence —}},
year = {2011}
}
@inproceedings{LiMa11-01,
abstract = {In this paper we report on the results of an automatic signature verification system on data of the ‘ICFHR 2010 4NSigComp’ forensic signature verification competition. The goal of this competition was to estimate the performance of automated systems in detecting skilled forgeries from genuine signatures of a reference writer. Unlike previous research in the field of signature verification, where the task was generally to separate the genuine signatures from the forged ones, another equally important category of forgery, namely the disguised signatures was also addressed in this competition. A disguised signature is a signature written by the authentic author but with the intention of possible denial at a later date. The system described in this paper did not participate in the competition, since it has been originally designed by the organizers of the competition. As an interesting outcome of the experiments, the system could achieve better equal error rates that any of the other submitted systems. The somewhat surprising fact is that the system has not been adapted to detect disguised signatures; it has originally been created for the task of detecting simulated and authentic signatures. We strongly believe that the main reason for the good performance is the difference that our system is relying on local features.},
author = {Liwicki, Marcus and {Imran Malik}, Muhammad},
booktitle = {Proc. 15th Conf. of the Int. Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Imran Malik/2011/Proc. 15th Conf. of the Int. Graphonomics Society/2011 - Liwicki, Imran Malik - Surprising Power of Local Features for Automated Signature Verification.pdf:pdf},
pages = {18--21},
title = {{Surprising ? Power of Local Features for Automated Signature Verification}},
year = {2011}
}
@inproceedings{KlLiGoMeWeDe11,
abstract = {This paper proposes a novel digital system for ordering customized products in a convenient pen and paper setting. In particular we integrate pen-based interaction forms which automatically recognize natural handwriting. The integration of these forms in a factory environment describes a novel way of addressing orders to a producing facility beside usual ways like direct access or web-interaction forms.},
author = {Koessling, Holger and Liwicki, Marcus and Gorecky, Dominic and Meixner, Gerrit and Weber, Markus and Dengel, Andreas},
booktitle = {18th IFAC World Congress Milano (Italy)},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Koessling et al/2011/18th IFAC World Congress Milano (Italy)/2011 - Koessling et al. - Pen-Based Interaction Forms for Smarter Product Customization.pdf:pdf},
keywords = {bluetooth,device,graphical user interfaces,handwriting,human-computer-interaction,input devices and,interaction techniques,natural user interfaces,pen based interaction,portable devices,smartfactorykl,strategies,universal interaction},
pages = {3974--3979},
publisher = {IFAC},
title = {{Pen-Based Interaction Forms for Smarter Product Customization}},
year = {2011}
}
@inproceedings{SoLiWe11-02,
abstract = {We present a digital pen based interface for clinical radiology reports in the field of mammography. It is of utmost importance in future radiology practices that the radiology reports be uniform, comprehensive, and easily managed. This means that reports must be "readable" to humans and machines alike. In order to improve reporting practices in mammography, we allow the radiologist to write structured reports with a special pen on paper with an invisible dot pattern. A handwriting software takes care of the interpretation of the written report which is transferred into an ontological representation. In addition, a gesture recogniser allows radiologists to encircle predefined annotation suggestions which turns out to be the most beneficial feature. The radiologist can (1) provide the image and image region annotations mapped to a FMA, RadLex, or ICD10 code, (2) provide free text entries, and (3) correct/select annotations while using multiple gestures on the forms and sketch regions. The resulting, automatically generated PDF report is then stored in a semantic backend system for further use and contains all transcribed annotations as well as all free form sketches.},
author = {Sonntag, Daniel and Liwicki, Marcus and Weber, Markus},
booktitle = {Proceedings of the 13th international conference on multimodal interfaces},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Sonntag, Liwicki, Weber/2011/Proceedings of the 13th international conference on multimodal interfaces/2011 - Sonntag, Liwicki, Weber - Digital Pen in Mammography Patient Forms.pdf:pdf},
isbn = {9781450306416},
keywords = {Pen/Ink Interface,design,ink interface,medical healthcare,pen},
pages = {303--306},
publisher = {ACM},
title = {{Digital Pen in Mammography Patient Forms}},
url = {http://dl.acm.org/citation.cfm?id=2070537},
year = {2011}
}
@article{Liwicki2010,
abstract = {In this paper, the problem of classifying handwritten data with respect to gender is addressed. A classification method based on Gaussian Mixture Models is applied to distinguish between male and female handwriting. Two sets of features using on-line and off-line information have been used for the classification. Furthermore, we combined both feature sets and investigated several combination strategies. In our experiments, the on-line features produced a higher classification rate than the offline features. However, the best results were obtained with the combination. The final gender detection rate on the test set is 67.57\%, which is significantly higher than the performance of the on-line and off-line system with about 64.25 and 55.39\%, respectively. The combined system also shows an improved performance over human-based classification. To the best of the authors’ knowledge, the system presented in this paper is the first completely automatic gender detection system which works on on-line data. Furthermore, the combination of on-line and off-line features for gender detection is investigated for the first time in the literature.},
author = {Liwicki, Marcus and Schlapbach, Andreas and Bunke, Horst},
doi = {10.1007/s10044-010-0178-6},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Schlapbach, Bunke/2011/Pattern Analysis and Applications/2011 - Liwicki, Schlapbach, Bunke - Automatic gender detection using on-line and off-line information.pdf:pdf},
issn = {1433-7541},
journal = {Pattern Analysis and Applications},
keywords = {analysis,gaussian mixture models,gender detection handwriting,multiple classifier combination},
month = apr,
number = {1},
pages = {87--92},
title = {{Automatic gender detection using on-line and off-line information}},
url = {http://www.springerlink.com/index/10.1007/s10044-010-0178-6},
volume = {14},
year = {2011}
}
@article{Liwicki2009,
author = {Liwicki, Marcus and Bunke, Horst},
doi = {10.1016/j.patcog.2008.10.030},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2009/Pattern Recognition/2009 - Liwicki, Bunke - Combining diverse on-line and off-line systems for handwritten text line recognition.pdf:pdf},
issn = {00313203},
journal = {Pattern Recognition},
keywords = {multiple classifier combination,off-line handwriting recognition,on-line handwriting recognition},
month = dec,
number = {12},
pages = {3254--3263},
title = {{Combining diverse on-line and off-line systems for handwritten text line recognition}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0031320308004652},
volume = {42},
year = {2009}
}
@inproceedings{SoLiWe11,
abstract = {This paper presents a pen-based interface for clinical radiologists. It is of utmost importance in future radiology practices that the radiology reports be uniform, comprehensive, and easily managed. This means that reports must be "readable" to humans and machines alike. In order to improve reporting practices, we allow the radiologist to write structured reports with a special pen on normal paper. A handwriting recognition and interpretation software takes care of the interpretation of the written report which is transferred into an ontological representation. The resulting report is then stored in a semantic backend system for further use. We will focus on the pen-based interface and new interaction possibilities with gestures in this scenario.},
author = {Sonntag, Daniel and Liwicki, Marcus and Weber, Markus},
booktitle = {Proceedings of the 16th International Conference on Intelligent User Interfaces},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Sonntag, Liwicki, Weber/2011/Proceedings of the 16th International Conference on Intelligent User Interfaces/2011 - Sonntag, Liwicki, Weber - Interactive Paper for Radiology Findings.pdf:pdf},
keywords = {design,medical healthcare,pen/ink interface},
pages = {459--460},
publisher = {ACM},
title = {{Interactive Paper for Radiology Findings}},
year = {2011}
}
@inproceedings{LiWeDe11,
abstract = {In this paper we describe a system which allows for intuitive pen input for human-machine-interaction on multi-touch surfaces. The system automatically analyzes the handwritten strokes and detects if they correspond to handwriting or to graphics or symbols. We propose an architecture which integrates this online mode detection system into a software development kit (SDK) to ease the design of pen-based applications. This novel toolkit allows for automated ink interpretation including handwriting recognition and shape detection. We have evaluated our system on a set of 1,600 handwritten words and symbols and integrated this system into a running demonstration prototype.},
author = {Liwicki, Marcus and Weber, Markus and Dengel, Andreas},
booktitle = {Proc. 15th Conf. of the International Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Weber, Dengel/2011/Proc. 15th Conf. of the International Graphonomics Society/2011 - Liwicki, Weber, Dengel - Online Mode Detection for Pen-Enabled Multi-Touch Interfaces.pdf:pdf},
pages = {18--21},
title = {{Online Mode Detection for Pen-Enabled Multi-Touch Interfaces}},
year = {2011}
}
@inproceedings{Uchida2010,
author = {Uchida, Seiichi and Liwicki, Marcus},
booktitle = {20th International Conference on Pattern Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Uchida, Liwicki/2010/20th International Conference on Pattern Recognition/2010 - Uchida, Liwicki - Analysis of Part-Based Features for Handwritten Character Recognition.pdf:pdf},
pages = {1945--1948},
title = {{Analysis of Part-Based Features for Handwritten Character Recognition}},
year = {2010}
}
@inproceedings{LiSchDeWeSiNo08-02,
abstract = {In this demo we present a system which recognizes and interprets the semantics of handwritten annotations on printed documents. The semantic information is sent to the Semantic Desktop, the personal Semantic Web on the desktop computer, which supports users in their information management. This allows a seamless integration of interactive paper into the individual knowledge work. The current implementation of the proposed system works with OpenOffice documents printed on Anoto paper. The system properties and a use case are described in this paper.},
author = {Liwicki, Marcus and Schumacher, Kinga and Dengel, Andreas and Weibel, Nadir and Signer, Beat and Norrie, Moria C},
booktitle = {Handout of 8th Int. Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2008/Handout of 8th Int. Workshop on Document Analysis Systems/2008 - Liwicki et al. - DEMO Semantic eInk Pen and Paper-based Interaction with the Semantic Desktop.pdf:pdf},
pages = {38--40},
title = {{DEMO: Semantic eInk: Pen and Paper-based Interaction with the Semantic Desktop}},
year = {2008}
}
@inproceedings{LiUcIwOmKi10-03,
author = {Liwicki, Marcus and Uchida, Seiichi and Iwamura, Masakazu and Omachi, Shinichiro and Kise, Koichi},
booktitle = {12th International Conference on Frontiers in Handwriting Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2010/12th International Conference on Frontiers in Handwriting Recognition/2010 - Liwicki et al. - Embedding Meta-Information in Handwriting --- Reed-Solomon for Reliable Error Correction.pdf:pdf},
pages = {51--56},
title = {{Embedding Meta-Information in Handwriting --- Reed-Solomon for Reliable Error Correction}},
year = {2010}
}
@article{SchLiBu07-01,
author = {Schlapbach, Andreas and Liwicki, Marcus and Bunke, Horst},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Schlapbach, Liwicki, Bunke/2008/Pattern Recognition/2008 - Schlapbach, Liwicki, Bunke - A Writer Identification System for On-line Whiteboard Data.pdf:pdf},
journal = {Pattern Recognition},
number = {7},
pages = {2381--2397},
title = {{A Writer Identification System for On-line Whiteboard Data}},
volume = {41},
year = {2008}
}
@inproceedings{Li09-01,
author = {Liwicki, Marcus},
booktitle = {5th Joint Workshop on Machine Perception and Robotics},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki/2009/5th Joint Workshop on Machine Perception and Robotics/2009 - Liwicki - Enhancing a Multi-touch Table with Write Functionality.pdf:pdf},
pages = {5 pages},
title = {{Enhancing a Multi-touch Table with Write Functionality}},
year = {2009}
}
@inproceedings{UcLiVi10-01,
author = {Uchida, Seiichi and Liwicki, Marcus and Marsault, Vincent},
booktitle = {Technical Committee on Pattern Recognition and Media Understanding},
pages = {6 pages},
title = {{Part-based handwritten numeral recognition}},
year = {2010}
}
@article{LiBu09-01,
abstract = {In this paper we describe feature selection experiments for online handwriting recognition. We investigated a set of 25 online and pseudo-offline features to find out which features are important and which features may be redundant. To analyze the saliency of the features we applied a sequential forward and a sequential backward search on the feature set. A hidden Markov model and a neural network based recognizer have been used as recognition engines. In our experiments we obtained interesting results. Using a set of only five features, we achieved a performance similar to that of the reference system that uses all 25 features. The five selected features have a low correlation and have been the top choices during the first iterations of the forward search with both recognizers. Furthermore, for both recognizers subsets have been identified that outperform the reference system with statistical significance. In order to assess the results more rigorously, we have compared our recognizer with the widely used commercial recognizer from Microsoft.},
author = {Liwicki, Marcus and Bunke, Horst},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2009/Int. Journal of Pattern Recognition and Artificial Intelligence/2009 - Liwicki, Bunke - Feature Selection for \{HMM\} and \{BLSTM\} based Handwriting Recognition of Whiteboard Notes.pdf:pdf},
journal = {Int. Journal of Pattern Recognition and Artificial Intelligence},
number = {5},
pages = {907--923},
title = {{Feature Selection for \{HMM\} and \{BLSTM\} based Handwriting Recognition of Whiteboard Notes}},
volume = {23},
year = {2009}
}
@inbook{LiBu10-02,
abstract = {In this chapter we describe various methods for the automatic recognition of handwritten whiteboard notes. A handwriting recognition system for Roman Script is usually divided into units which iteratively process the handwritten input data to finally obtain the desired ASCII transcription: the preprocessing, where noise in the raw data is reduced; the normalization, where various steps take place to remove writer-specific characteristics of the handwriting; the feature extraction, where the normalized data is transformed into a sequence of feature vectors; the recognition, where a classifier generates a list of word sequence candidates; and the post-processing, where language information is used to improve the results. We review different approaches for all of these stages and describe selected approaches in more detail. Furthermore, we introduce some preprocessing steps which have been developed especially for whiteboard notes. In order to assess the advantages of different methods, we present the results of a broad experimental analysis on a large database of handwritten whiteboard notes.},
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {C H Chen; : Handbook of Pattern Recognition and Computer Vision},
chapter = {3.5},
edition = {4},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2010/C H Chen Handbook of Pattern Recognition and Computer Vision/2010 - Liwicki, Bunke - Recognition Techniques for Whiteboard Notes Written in Roman Script.pdf:pdf},
isbn = {978-981-4273-38-1},
pages = {397--414},
publisher = {World Scientific},
title = {{Recognition Techniques for Whiteboard Notes Written in Roman Script}},
year = {2010}
}
@inproceedings{FiWuLiFrBuViSt09-01,
address = {Los Alamitos, CA, USA},
author = {Fischer, Andreas and Wuthrich, Markus and Liwicki, Marcus and Frinken, Volkmar and Bunke, Horst and Viehhauser, Gabriel and Stolz, Michael},
booktitle = {Virtual Systems and MultiMedia, International Conference on},
doi = {http://doi.ieeecomputersociety.org/10.1109/VSMM.2009.26},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Fischer et al./2009/Virtual Systems and MultiMedia, International Conference on/2009 - Fischer et al. - Automatic Transcription of Handwritten Medieval Documents.pdf:pdf},
isbn = {978-0-7695-3790-0},
pages = {137--142},
publisher = {IEEE Computer Society},
title = {{Automatic Transcription of Handwritten Medieval Documents}},
year = {2009}
}
@inproceedings{LiBu05-02,
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 8th Int. Conf. on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2005/Proc. 8th Int. Conf. on Document Analysis and Recognition/2005 - Liwicki, Bunke - Enhancing Training Data for Handwriting Recognition of Whiteboard Notes with Samples from a Different Da.pdf:pdf},
pages = {550--554},
title = {{Enhancing Training Data for Handwriting Recognition of Whiteboard Notes with Samples from a Different Database}},
volume = {2},
year = {2005}
}
@inproceedings{LiUcIwOmKi10-02,
author = {Liwicki, Marcus and Uchida, Seiichi and Iwamura, Masakazu and Omachi, Shinichiro and Kise, Koichi},
booktitle = {9th Int. Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2010/9th Int. Workshop on Document Analysis Systems/2010 - Liwicki et al. - Data-Embedding Pen --- Augmenting Ink Strokes with Meta-Information.pdf:pdf},
pages = {43--52},
title = {{Data-Embedding Pen --- Augmenting Ink Strokes with Meta-Information}},
year = {2010}
}
@inproceedings{UcLi10-02,
author = {Uchida, Seiichi and Liwicki, Marcus},
booktitle = {12th International Conference on Frontiers in Handwriting Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Uchida, Liwicki/2010/12th International Conference on Frontiers in Handwriting Recognition/2010 - Uchida, Liwicki - Part-Based Recognition of Handwritten Characters.pdf:pdf},
pages = {545--550},
title = {{Part-Based Recognition of Handwritten Characters}},
year = {2010}
}
@inproceedings{LiSchlBu06-01,
author = {Liwicki, Marcus and Schlapbach, Andreas and Bunke, Horst and Bengio, Samy and Mari\'{e}thoz, Jonny and Richiardi, Jonas},
booktitle = {Proc. 7th IAPR Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2006/Proc. 7th IAPR Workshop on Document Analysis Systems/2006 - Liwicki et al. - Writer Identification for Smart Meeting Room Systems.pdf:pdf},
pages = {186--195},
publisher = {Springer},
series = {LNCS},
title = {{Writer Identification for Smart Meeting Room Systems}},
volume = {3872},
year = {2006}
}
@article{LiBu09-02,
annote = {published online},
author = {Liwicki, Marcus and Bunke, Horst and Pittman, James A and Knerr, Stefan},
doi = {http://dx.doi.org/10.1007/s00138-009-0208-9},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al/2011/Machine Vision and Applications/2011 - Liwicki et al. - Combining Diverse Systems for Handwritten Text Line Recognition.pdf:pdf},
journal = {Machine Vision and Applications},
number = {1},
pages = {39--51},
publisher = {Springer Berlin / Heidelberg},
title = {{Combining Diverse Systems for Handwritten Text Line Recognition}},
volume = {22},
year = {2011}
}
@inproceedings{KnLi06-01,
author = {Knipping, Lars and Liwicki, Marcus},
booktitle = {Int. Symposium on Multimedia},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Knipping, Liwicki/2006/Int. Symposium on Multimedia/2006 - Knipping, Liwicki - Chalklets Developing Applications for a Board Environment.pdf:pdf},
pages = {907--914},
publisher = {IEEE},
title = {{Chalklets: Developing Applications for a Board Environment}},
year = {2006}
}
@inproceedings{LiKn05-01,
author = {Liwicki, Marcus and Knipping, Lars},
booktitle = {Proc. 9th Int. Conf. on Knowledge-Based Intelligent Information \& Engineering Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Knipping/2005/Proc. 9th Int. Conf. on Knowledge-Based Intelligent Information \& Engineering Systems/2005 - Liwicki, Knipping - Recognizing and Simulating Sketched Logic Circuits.pdf:pdf},
pages = {588--594},
publisher = {Springer},
series = {LNCS},
title = {{Recognizing and Simulating Sketched Logic Circuits}},
url = {http://www.springerlink.com/openurl.asp?genre=article\&id=doi:10.1007/11553939\_84},
volume = {3683},
year = {2005}
}
@inproceedings{InLiBu08-01,
abstract = {In this paper we propose a recognition system for handwritten manuscripts by writers of the 20th century. The proposed system first applies some preprocessing steps to remove background noise. Next the pages are segmented into individual text lines. After normalization a hidden Markov model based recognizer, supported by a language model, is applied to each text line. In our experiments we investigate two approaches for training the recognition system. The first approach consists in training the recognizer directly from scratch, while the second adapts it from a recognizer previously trained on a large general off-line handwriting database. The second approach is unconventional in the sense that the language of the texts used for training is different from that used for testing. In our experiments with several training sets of increasing size we found that the overall best strategy is adapting the previously trained recognizer on a writer specific data set of medium size. The final word recognition accuracy obtained with this training strategy is about 80\%.},
author = {Inderm\"{u}hle, Emanuel and Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 11th Int. Conference on Frontiers in Handwriting Recognition},
pages = {186--191},
title = {{Recognition of Handwritten Historical Documents: \{HMM\}-Adaptation vs. Writer Specific Training}},
year = {2008}
}
@inproceedings{Li10-03,
author = {Liwicki, Marcus},
booktitle = {Technical Committee on Pattern Recognition and Media Understanding},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki/2010/Technical Committee on Pattern Recognition and Media Understanding/2010 - Liwicki - Integrating Touch and Write into a Single Multitouch Surface.pdf:pdf},
pages = {5 pages},
title = {{Integrating Touch and Write into a Single Multitouch Surface}},
year = {2010}
}
@inproceedings{LiBu05-03,
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 8th Int. Conf. on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2005/Proc. 8th Int. Conf. on Document Analysis and Recognition/2005 - Liwicki, Bunke - \{IAM-OnDB\} -- an On-Line \{English\} Sentence Database Acquired from Handwritten Text on a Whiteboard.pdf:pdf},
pages = {956--961},
title = {{\{IAM-OnDB\} -- an On-Line \{English\} Sentence Database Acquired from Handwritten Text on a Whiteboard}},
volume = {2},
year = {2005}
}
@inproceedings{GrFeSchLiBu07-01,
author = {Graves, Alex and Fernandez, Santiago and Liwicki, Marcus and Bunke, Horst and Schmidhuber, J\"{u}rgen},
booktitle = {Advances in Neural Information Processing Systems 20},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Graves et al./2008/Advances in Neural Information Processing Systems 20/2008 - Graves et al. - Unconstrained online handwriting recognition with recurrent neural networks.pdf:pdf},
pages = {577--584},
publisher = {MIT Press},
title = {{Unconstrained online handwriting recognition with recurrent neural networks}},
year = {2008}
}
@inproceedings{LiBu06-01,
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 10th Int. Workshop on Frontiers in Handwriting Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2006/Proc. 10th Int. Workshop on Frontiers in Handwriting Recognition/2006 - Liwicki, Bunke - \{HMM\}-Based On-Line Recognition of Handwritten Whiteboard Notes.pdf:pdf},
pages = {595--599},
title = {{\{HMM\}-Based On-Line Recognition of Handwritten Whiteboard Notes}},
year = {2006}
}
@inproceedings{LiRoElDe10-01,
author = {Liwicki, Marcus and Rostanin, Oleg and El-Neklawy, Saher Mohamed and Dengel, Andreas},
booktitle = {9th Int. Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al/2010/9th Int. Workshop on Document Analysis Systems/2010 - Liwicki et al. - Touch \{\&\} Write a Multi-Touch Table with Pen-Input.pdf:pdf},
pages = {479--484},
title = {{Touch \{\&\} Write: a Multi-Touch Table with Pen-Input}},
year = {2010}
}
@inproceedings{WeLiDe10-01,
abstract = {Architects’ daily routine means working with drawings. They use either a pen or a computer sketching their ideas or drawing to scale. When beginning a new project they often have to search for similar projects in the past. In this paper a sketch-based approach is proposed to query the floor plan repository. The user searches for semantically similar floor plans just by drawing the new plan. An algorithm extracts the semantic structure sketched by the architect on DFKI’s Touch \& Write table and compares the structure of the sketch with the ones from the floor plan repository. The a.SCatch system enables the user to easily access knowledge from past projects. While in the current pro- totype only sketches with a predefined structure are recognized, we will extend the system to work with normal floor plans.},
author = {Weber, Markus and Liwicki, Marcus and Dengel, Andreas},
booktitle = {12th International Conference on Frontiers of Handwriting Recognition.},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Weber, Liwicki, Dengel/2010/12th International Conference on Frontiers of Handwriting Recognition./2010 - Weber, Liwicki, Dengel - a.SCAtch - A Sketch-Based Retrieval for Architectural Floor Plans.pdf:pdf},
pages = {289--294},
title = {{a.SCAtch - A Sketch-Based Retrieval for Architectural Floor Plans}},
year = {2010}
}
@inproceedings{Li09-02,
author = {Liwicki, Marcus},
booktitle = {Proc. 14th Conf. of the Int. Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki/2009/Proc. 14th Conf. of the Int. Graphonomics Society/2009 - Liwicki - Evaluation of Novel Features and Different Models for Online Signature Verification in a Real-World Scenario.pdf:pdf},
pages = {22--25},
title = {{Evaluation of Novel Features and Different Models for Online Signature Verification in a Real-World Scenario}},
year = {2009}
}
@inproceedings{LiSchDeWeSiNo08-01,
abstract = {In this paper we propose a system which recognizes and interprets the semantics of handwritten annotations on printed documents. The semantic information will be sent to the Semantic Desktop, the personal Semantic Web on the desktop computer, which supports users in their information management. This allows a seamless integration of interactive paper into the individual knowledge work. The current implementation of the proposed system works with OpenOffice documents printed on Anoto paper. However, our system generally works on any kind of interactive paper documents and the support of other document formats is planned in near future.},
author = {Liwicki, Marcus and Schumacher, Kinga and Dengel, Andreas and Weibel, Nadir and Signer, Beat and Norrie, Moria C},
booktitle = {Handout of 8th Int. Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2008/Handout of 8th Int. Workshop on Document Analysis Systems/2008 - Liwicki et al. - Pen and Paper-based Interaction with the Semantic Desktop.pdf:pdf},
pages = {2--5},
title = {{Pen and Paper-based Interaction with the Semantic Desktop}},
year = {2008}
}
@inproceedings{LiWeDe09-01,
author = {Liwicki, Marcus and Weber, Markus and Dengel, Andreas},
booktitle = {KI},
pages = {581--588},
title = {{Automatic Recognition and Interpretation of Pen- and Paper-Based Document Annotations}},
year = {2009}
}
@article{LiBu07-01,
author = {Liwicki, Marcus and Bunke, Horst},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2007/Int. Journal of Pattern Recognition and Artificial Intelligence/2007 - Liwicki, Bunke - Handwriting Recognition of Whiteboard Notes -- Studying the Influence of Training Set Size and Typ.pdf:pdf},
journal = {Int. Journal of Pattern Recognition and Artificial Intelligence},
number = {1},
pages = {83--98},
title = {{Handwriting Recognition of Whiteboard Notes -- Studying the Influence of Training Set Size and Type}},
volume = {21},
year = {2007}
}
@inproceedings{WuLiFiInBuViSt09,
abstract = {Building recognition systems for historical documents is a difficult task. Especially, when it comes to medieval scripts. The complexity is mainly affected by the poor quality and the small quantity of the data available. In this paper we apply an HMM based recognition system to medieval manuscripts from the 13th century written in Middle High German. The recognition system, which was originally developed for modern scripts, has been adapted to medieval scripts. Beside the data processing, one of the major challenges is to create a suitable language model. Because of the lack of appropriate independent text corpora for medieval languages, the language model has to be created on the base of a rather small number of manuscripts only. Due to the small size of the corpus, optimizing the language model parameters can quickly lead to the problem of overfitting. In this paper we describe a strategy to integrate all available information into the language model and to optimize the language model parameters without suffering from this problem.},
address = {Washington, DC, USA},
author = {W\"{u}thrich, Markus and Liwicki, Marcus and Fischer, Adreas and Inderm\"{u}hle, Emanuel and Bunke, Horst and Viehhauser, Gabriel and Stolz, Michael},
booktitle = {10th Int. Conf. on Document Analysis and Recognition},
doi = {http://dx.doi.org/10.1109/ICDAR.2009.17},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/W\"{u}thrich et al./2009/10th Int. Conf. on Document Analysis and Recognition/2009 - W\"{u}thrich et al. - Language Model Integration for the Recognition of Handwritten Medieval Documents.pdf:pdf},
isbn = {978-0-7695-3725-2},
pages = {211--215},
publisher = {IEEE Computer Society},
title = {{Language Model Integration for the Recognition of Handwritten Medieval Documents}},
year = {2009}
}
@inproceedings{LiDe09-01,
author = {Liwicki, Marcus and Dengel, Andreas},
booktitle = {Proc. 14th Conf. of the Int. Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Dengel/2009/Proc. 14th Conf. of the Int. Graphonomics Society/2009 - Liwicki, Dengel - Requirements for Intelligent Pen-Based Annotation Systems --- An Exemplary Study with Semantic eInk.pdf:pdf},
pages = {234--237},
title = {{Requirements for Intelligent Pen-Based Annotation Systems --- An Exemplary Study with Semantic eInk}},
year = {2009}
}
@inproceedings{InLiBu10-01,
author = {Inderm\"{u}hle, Emanuel and Liwicki, Marcus and Bunke, Horst},
booktitle = {9th Int. Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Inderm\"{u}hle, Liwicki, Bunke/2010/9th Int. Workshop on Document Analysis Systems/2010 - Inderm\"{u}hle, Liwicki, Bunke - \{IAMonDo\}-Database an Online Handwritten Document Database with Non-Uniform Contents.pdf:pdf},
pages = {97--104},
title = {{\{IAMonDo\}-Database: an Online Handwritten Document Database with Non-Uniform Contents}},
year = {2010}
}
@inproceedings{EbLiDe10-01,
author = {Ebert, Sebastian and Liwicki, Marcus and Dengel, Andreas},
booktitle = {12th International Conference on Frontiers in Handwriting Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Ebert, Liwicki, Dengel/2010/12th International Conference on Frontiers in Handwriting Recognition/2010 - Ebert, Liwicki, Dengel - Ontology-Based Information Extraction from Handwritten Documents.pdf:pdf},
pages = {483--488},
title = {{Ontology-Based Information Extraction from Handwritten Documents}},
year = {2010}
}
@inproceedings{LiSchBu08-01,
abstract = {In this paper we present a writer-dependent handwriting recognition system based on hidden Markov models (HMMs). This system, which has been developed in the context of research on smart meeting rooms, operates in two stages. First, a Gaussian mixture model (GMM)-based writer identification system developed for smart meeting rooms identifies the person writing on the whiteboard. Then a recognition system adapted to the individual writer is applied. Two different methods for obtaining writer-dependent recognizers are proposed. The first method uses the available writer-specific data to train an individual recognition system for each writer from scratch, while the second method takes a writer-independent recognizer and adapts it with the data from the considered writer. The experiments have been performed on the IAM-OnDB. In the first stage, the writer identification system produces a perfect identification rate. In the second stage, the writer-specific recognition system gets significantly better recognition results, compared to the writer-independent recognizer. The final word recognition rate on the IAM-OnDB-t1 benchmark task is close to 80$\backslash$,\%.},
author = {Liwicki, Marcus and Schlapbach, Andreas and Bunke, Horst},
booktitle = {Proc. 8th IAPR Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Schlapbach, Bunke/2008/Proc. 8th IAPR Workshop on Document Analysis Systems/2008 - Liwicki, Schlapbach, Bunke - Writer-Dependent Recognition of Handwritten Whiteboard Notes in Smart Meeting Room En.pdf:pdf},
pages = {151--157},
title = {{Writer-Dependent Recognition of Handwritten Whiteboard Notes in Smart Meeting Room Environments}},
year = {2008}
}
@book{LiBu08,
abstract = {This book addresses the issue of processing online handwritten notes acquired from an electronic whiteboard. Notes written on a whiteboard is a new modality in handwriting recognition research that has received relatively little attention in the past. The main motivation for this book is smart meeting room applications, where not only speech and video data of a meeting are recorded, but also notes written on a whiteboard are captured. The aim of a smart meeting room is to automate standard tasks usually performed by humans in a meeting. In order to allow for retrieval of the meeting data by means of a browser, semantic information needs to be extracted from the raw sensory data. The main achievements of this book can be summarized as follows. A new online handwritten database has been compiled, and four handwriting recognition systems have been developed. These are an offline and an online recognition system, a system combining offline and online data, and a writer-dependent recognition system. The online recognition system includes novel preprocessing and normalization strategies which have been developed especially for whiteboard notes. A novel classification strategy based on bidirectional long short-term memory networks has been applied for the first time in the field of handwriting recognition. In the combination experiments both the offline and online system were integrated into a single recognizer. To the best of the authors' knowledge these are the first experiments in the field of online sentence recognition combining systems based on offline and online features. Furthermore, external recognition systems were included in the combination experiments. The experimental results on the test set show a highly significant improvement of the recognition performance over the individual systems. The optimal combination achieved a word level accuracy of more than 86$\backslash$,\%, implying a relative error reduction of about 26$\backslash$,\%, compared to the best individual classifier.},
author = {Liwicki, Marcus and Bunke, Horst},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2008/Unknown/2008 - Liwicki, Bunke - RECOGNITION OF WHITEBOARD NOTES - Online, Offline and Combination.pdf:pdf},
publisher = {World Scientific},
series = {In Series in Machine Perception and Artificial Intelligence},
title = {{RECOGNITION OF WHITEBOARD NOTES - Online, Offline and Combination}},
volume = {71},
year = {2008}
}
@inproceedings{LiBu05-01,
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 12th Conf. of the Int. Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2005/Proc. 12th Conf. of the Int. Graphonomics Society/2005 - Liwicki, Bunke - Handwriting Recognition of Whiteboard Notes.pdf:pdf},
pages = {118--122},
title = {{Handwriting Recognition of Whiteboard Notes}},
year = {2005}
}
@inproceedings{LiInBu07-01,
author = {Liwicki, Marcus and Inderm\"{u}hle, Emanuel and Bunke, Horst},
booktitle = {Proc. 9th Int. Conf. on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Inderm\"{u}hle, Bunke/2007/Proc. 9th Int. Conf. on Document Analysis and Recognition/2007 - Liwicki, Inderm\"{u}hle, Bunke - On-Line Handwritten Text Line Detection Using Dynamic Programming.pdf:pdf},
pages = {447--451},
title = {{On-Line Handwritten Text Line Detection Using Dynamic Programming}},
volume = {1},
year = {2007}
}
@inproceedings{SchuLiDe09,
author = {Schumacher, Kinga and Liwicki, Marcus and Dengel, Andreas},
booktitle = {Proceedings of the 5th Conference on Professional Knowledge Management},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Schumacher, Liwicki, Dengel/2009/Proceedings of the 5th Conference on Professional Knowledge Management/2009 - Schumacher, Liwicki, Dengel - A Paper-based Technology for Personal Knowledge Management.pdf:pdf},
pages = {289--298},
series = {LNI},
title = {{A Paper-based Technology for Personal Knowledge Management}},
volume = {P-145},
year = {2009}
}
@inproceedings{WeLaRoLiDePe10-01,
abstract = {The aim of the a.SCatch system is to implement a seman- tic search for architectural floor plans. Therefore a semantic structure describing the content of a floor plan is proposed. A prototypical ap- plication for a semi-automatic extraction of this structure from existing projects is provided by extracting this information from standard file formats used in architecture. Architects daily routine means working with drawings. They use either pen or computer to sketch their ideas or to draw to scale. Thus a sketch- based approach is proposed to query the floor plan repository. The user of the system will be able to search for semantically similar floor plans by sketching a floor plan. Therefore an algorithm extracts the semantic structure sketched by the architect on the user interface and compares the structure of the sketch with the ones from the floor plan repository. The system will enable the user to easily access knowledge from past projects.},
author = {Weber, Markus and Langenhan, Christoph and Roth-Berghofer, Thomas and Liwicki, Marcus and Dengel, Andreas and Petzold, Frank},
booktitle = {ICCBR},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Weber et al./2010/ICCBR/2010 - Weber et al. - \{a.SCatch\} Semantic Structure for Architectural Floor Plan Retrieval.pdf:pdf},
pages = {510--524},
title = {{\{a.SCatch\}: Semantic Structure for Architectural Floor Plan Retrieval}},
year = {2010}
}
@inproceedings{LiAbDe10-01,
author = {Liwicki, Marcus and Eisha, Hassan Mohamed Abou and Dengel, Andreas},
booktitle = {9th Int. Workshop on Document Analysis Systems},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Eisha, Dengel/2010/9th Int. Workshop on Document Analysis Systems/2010 - Liwicki, Eisha, Dengel - Improving Handwriting Recognition by the use of Semantic Information.pdf:pdf},
pages = {441--446},
title = {{Improving Handwriting Recognition by the use of Semantic Information}},
year = {2010}
}
@inproceedings{LiBu07-03,
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 13th Conf. of the Int. Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2007/Proc. 13th Conf. of the Int. Graphonomics Society/2007 - Liwicki, Bunke - Feature Selection for On-Line Handwriting Recognition of Whiteboard Notes.pdf:pdf},
pages = {101--105},
title = {{Feature Selection for On-Line Handwriting Recognition of Whiteboard Notes}},
year = {2007}
}
@inproceedings{LiSchLoBu07-01,
author = {Liwicki, Marcus and Schlapbach, Andreas and Loretan, Peter and Bunke, Horst},
booktitle = {Proc. 13th Conf. of the Int. Graphonomics Society},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2007/Proc. 13th Conf. of the Int. Graphonomics Society/2007 - Liwicki et al. - Automatic Detection of Gender and Handedness from On-Line Handwriting.pdf:pdf},
pages = {179--183},
title = {{Automatic Detection of Gender and Handedness from On-Line Handwriting}},
year = {2007}
}
@inproceedings{Li10-01,
author = {Liwicki, Marcus},
booktitle = {Technical Committee on Pattern Recognition and Media Understanding},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki/2010/Technical Committee on Pattern Recognition and Media Understanding/2010 - Liwicki - An Easy-To-Use Recurrent Neural Network Architecture for Sequence Recognition.pdf:pdf},
pages = {6 pages},
title = {{An Easy-To-Use Recurrent Neural Network Architecture for Sequence Recognition}},
year = {2010}
}
@inproceedings{LiHeFoMa10-01,
author = {Liwicki, Marcus and van den Heuvel, C Elisa and Found, Bryan and Malik, Muhammad Imran},
booktitle = {12th International Conference on Frontiers in Handwriting Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2010/12th International Conference on Frontiers in Handwriting Recognition/2010 - Liwicki et al. - Forensic Signature Verification Competition 4NSigComp2010 - Detection of Simulated and Disgu.pdf:pdf},
pages = {715--720},
title = {{Forensic Signature Verification Competition 4NSigComp2010 - Detection of Simulated and Disguised Signatures}},
year = {2010}
}
@inproceedings{LiGrBuSch07-01,
author = {Liwicki, Marcus and Graves, Alex and Bunke, Horst and Schmidhuber, J\"{u}rgen},
booktitle = {Proc. 9th Int. Conf. on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2007/Proc. 9th Int. Conf. on Document Analysis and Recognition/2007 - Liwicki et al. - A Novel Approach to On-Line Handwriting Recognition Based on Bidirectional Long Short-Term Memory Networ.pdf:pdf},
pages = {367--371},
title = {{A Novel Approach to On-Line Handwriting Recognition Based on Bidirectional Long Short-Term Memory Networks}},
volume = {1},
year = {2007}
}
@inproceedings{LiBu06-02,
author = {Liwicki, Marcus and Scherz, Matthias and Bunke, Horst},
booktitle = {Proc. 18th Int. Conf. on Pattern Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Scherz, Bunke/2006/Proc. 18th Int. Conf. on Pattern Recognition/2006 - Liwicki, Scherz, Bunke - Word Extraction from On-Line Handwritten Text Lines.pdf:pdf},
pages = {929--933},
title = {{Word Extraction from On-Line Handwritten Text Lines}},
volume = {2},
year = {2006}
}
@inproceedings{LiBu08-02,
abstract = {In this paper we present a multiple classifier system
(MCS) for on-line handwriting recognition. The MCS
combines several individual recognition systems based on
bidirectional long short-term memory networks. To obtain
diverse recognizers, we use different feature sets based on
on-line and off-line features. Furthermore, we generate
a number of different recognizers by changing the initialization
of the networks. To combine the word sequences
output by the recognizers, we incrementally align these
sequences using the recognizer output voting error reduction
framework (ROVER). For deriving the final decision,
different voting strategies are applied. The best combination
ensemble has a recognition rate of 83.64\%, which is
significantly higher than the 81.26\% achieved by the best
individual classifier.},
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 11th Int. Conference on Frontiers in Handwriting Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2008/Proc. 11th Int. Conference on Frontiers in Handwriting Recognition/2008 - Liwicki, Bunke - Combining On-Line and Off-Line Bidirectional Long Short-Term Memory Networks for Handwritten Te.pdf:pdf},
pages = {31--36},
title = {{Combining On-Line and Off-Line Bidirectional Long Short-Term Memory Networks for Handwritten Text Line Recognition}},
year = {2008}
}
@inproceedings{InLiBu09-01,
abstract = {In this paper we propose a new strategy for combining the outputs of several alignment systems. Based on the word boundaries retrieved from a number of individual alignment systems, the new boundaries are estimated. We investigate three strategies for this estimation. First, the mean value of the individual boundaries is taken, second the median is selected, and third, confidence values of the alignment systems are considered. We apply the combination strategies on a word mapping system for historical handwritten manuscripts. After some preprocessing and normalizing steps, three differently trained hidden Markov model based handwriting recognizers are applied to the text lines in forced alignment mode. As a result, the positions of the word boundaries are obtained. In in a number of experiments it is shown that a combination strategy based on the median outperforms the others and all individual alignment systems with a word mapping rate of about 95\%.},
author = {Inderm\"{u}hle, Emanuel and Liwicki, Marcus and Bunke, Horst},
booktitle = {10th Int. Conf. on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Inderm\"{u}hle, Liwicki, Bunke/2009/10th Int. Conf. on Document Analysis and Recognition/2009 - Inderm\"{u}hle, Liwicki, Bunke - Combining Alignment Results for Historical Handwritten Document Analysis.pdf:pdf},
pages = {1186--1190},
title = {{Combining Alignment Results for Historical Handwritten Document Analysis}},
year = {2009}
}
@inproceedings{LiUcIwOmKi10-01,
author = {Liwicki, Marcus and Uchida, Seiichi and Iwamura, Masakazu and Omachi, Shinichiro and Kise, Koichi},
booktitle = {Technical Committee on Pattern Recognition and Media Understanding},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki et al./2010/Technical Committee on Pattern Recognition and Media Understanding/2010 - Liwicki et al. - An Interface for Embedding Online Information During Writing.pdf:pdf},
pages = {6 pages},
title = {{An Interface for Embedding Online Information During Writing}},
year = {2010}
}
@article{GrLiFeBuSch08-01,
abstract = {Recognising lines of unconstrained handwritten text is a challenging task. The difficulty of segmenting cursive or overlapping characters, combined with the need to assimilate context information, has led to low recognition rates for even the best current recognisers. Most recent progress in the field has been made either through improved preprocessing, or through advances in language modelling. Relatively little work has been done on the basic recognition algorithms. Indeed, most systems rely on the same hidden Markov models that have been used for decades in speech and handwriting recognition, despite their well-known shortcomings. This paper proposes an alternative approach based on a novel type of recurrent neural network, specifically designed for sequence labelling tasks where the data is hard to segment and contains long-range, bidirectional interdependencies. In experiments on two unconstrained handwriting databases, the new approach achieves word recognition accuracies of 79.7\% on online data and 74.1\% on offline data, significantly outperforming a state-of-the-art HMM-based system. In addition, we demonstrate the network�s robustness to lexicon size, measure the influence of its hidden layers, and analyse its use of context. Lastly we provide an in-depth discussion of the differences between the network and HMMs, suggesting reasons for the network�s superior performance.},
address = {Los Alamitos, CA, USA},
author = {Graves, Alex and Liwicki, Marcus and Fern\'{a}ndez, Santiago and Bertolami, Roman and Bunke, Horst and Schmidhuber, J\"{u}rgen},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.137},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Graves et al/2009/IEEE Transactions on Pattern Analysis and Machine Intelligence/2009 - Graves et al. - A Novel Connectionist System for Unconstrained Handwriting Recognition.pdf:pdf},
issn = {0162-8828},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
number = {5},
pages = {855--868},
publisher = {IEEE Computer Society},
title = {{A Novel Connectionist System for Unconstrained Handwriting Recognition}},
volume = {31},
year = {2009}
}
@inproceedings{LiBu07-02,
author = {Liwicki, Marcus and Bunke, Horst},
booktitle = {Proc. 9th Int. Conf. on Document Analysis and Recognition},
file = {:C$\backslash$:/Users/liwicki/Documents/Mendeley Desktop/Liwicki, Bunke/2007/Proc. 9th Int. Conf. on Document Analysis and Recognition/2007 - Liwicki, Bunke - Combining On-Line and Off-Line Systems for Handwriting Recognition.pdf:pdf},
pages = {372--376},
title = {{Combining On-Line and Off-Line Systems for Handwriting Recognition}},
volume = {1},
year = {2007}
}
@article{UcLiIwShKi10-01,
author = {Uchida, Seiichi and Liwicki, Marcus and Iwamura, Masakazu and Omachi, Shinichiro and Kise, Koichi},
journal = {Journal of the Institute of Image Information and Television Engineers},
number = {3},
pages = {293--298},
title = {{Digital Pen Technologies (Japanese)}},
volume = {64},
year = {2010}
}