TPM Feature Set: a Universal Algorithm for Spatial-Temporal Pressure Mapping Imagery Data

Bo Zhou, Paul Lukowicz

In: IARIA. International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM-2019) September 22-26 Porto Portugal IARIA XPS Press 9/2019.


There have been many studies in recent years using the Textile planar Pressure Mapping (TPM) technology for computer-human interactions and ubiquitous activity recogni- tion. A TPM sensing system generates a time sequence of spatial pressure imagery. We propose a novel, comprehensive and unified feature set to evaluate TPM data from the space and time domain. The initial version of the TPM feature set presented in this paper includes 663 temporal features and 80 spatial features. We evaluated the feature set on 3 datasets from past studies in the scopes of ambient, smart object and wearable sensing. The TPM feature set has shown superior recognition accuracy compared with the ad-hoc algorithms from the corresponding studies. Furthermore, we have demonstrated the general approach to further reduce and optimise the feature calculation process for specific applications with neighbourhood component analysis.


Ubicomm19_TPM_Camera_Ready_v3.pdf (pdf, 8 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence