Recognizing Words in Scenes with a Head-Mounted Eye-Tracker
Takuya Kobayashi; Takumi Toyama; Faisal Shafait; Andreas Dengel; Masakazu Iwamura; Koichi Kise
In: IAPR International Workshop on Document Analysis Systems. IAPR International Workshop on Document Analysis Systems (DAS-12), 10th, March 27-29, Gold Coast, Queensland, Australia, IEEE, 3/2012.
Recognition of scene text using a hand-held camera is emerging as a hot topic of research. In this paper, we investigate the use of a head-mounted eye-tracker for scene text recognition. An eye-tracker detects the position of the users gaze. Using gaze information of the user, we can provide the user with more information about his region/object of interest in a ubiquitous manner. Therefore, we can realize a service such as the user gazes at a certain word and soon obtain the related information of the word by combining a word recognition system with eye-tracking technology. Such a service is useful since the user has to do nothing but gazes at interested words. With a view to realize the service, we experimentally evaluate the effectiveness of using the eye-tracker for word recognition. The initial results show the recognition accuracy was around 70% in our word recognition experiment and the average computational time was less than one second per a query image.