NDLI: Ontological representation of time-of-flight camera data to support vision-based AmI

Content Provider	IEEE Xplore Digital Library
Author	Serrano, M.A. Gomez-Romero, J. Patricio, M.A. Garcia, J. Molina, J.M.
Copyright Year	2012
Description	Author affiliation: Applied Artificial Intelligence Group (GIAA), Universidad Carlos III de Madrid, UC3M, Colmenarejo, Madrid, Spain (Serrano, M.A.; Gomez-Romero, J.; Patricio, M.A.; Garcia, J.; Molina, J.M.)
Abstract	Recent advances in technologies for capturing video data have opened a vast amount of new application areas. Among them, the incorporation of Time-of-Flight (ToF) cameras on Ambient Intelligence (AmI) environments. Although the performance of tracking algorithms have quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted for smart environments. This paper presents an extension of a previous system in the area of video-based AmI to incorporate ToF information to enhance scene interpretation. The framework is founded on an ontology-based model of the scene, which is extended to incorporate ToF data. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP) application.
Starting Page	865
Ending Page	870
File Size	201248
Page Count	6
File Format	PDF
ISBN	9781467309059
e-ISBN	9781467309073
e-ISBN	9781467309066
DOI	10.1109/PerComW.2012.6197633
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-19
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ontologies Biological system modeling Joints Cameras Computational modeling Data models Humans Social Signal Processing Visual sensor networks Time-of-Flight camera Ambient Intelligence
Content Type	Text
Resource Type	Article

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