Automatic semantic summarisation of human activity and detection of unusual inactivity are useful goals for a vision system operating in a supportive home environment. Learned models of spatial context are used in conjunction with a tracker to achieve these goals. The tracker uses a coarse ellipse model and a particle filter to cope with cluttered scenes with multiple sources of illumination. Summarisation in terms of semantic regions is demonstrated using acted scenes through automatic recovery of the instructions given to the actor. The use of 'unusual inactivity' detection as a cue for fall detection is also demonstrated.
|Title of host publication||Proceedings - International Conference on Pattern Recognition|
|Subtitle of host publication||Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004; Cambridge; United Kingdom; 23 August 2004 through 26 August 2004|
|Number of pages||4|
|Publication status||Published - 1 Jan 2004|
Nait-Charif, H., & McKenna, S. J. (2004). Activity summarisation and fall detection in a supportive home environment. In Proceedings - International Conference on Pattern Recognition: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004; Cambridge; United Kingdom; 23 August 2004 through 26 August 2004 (Vol. 4, pp. 323-326). IEEE. https://doi.org/10.1109/ICPR.2004.1333768