Alexander Artikis
ABSTRACT
We have been developing a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities detected on video frames. The output of our system is a set of recognised long-term activities, which are pre-defined temporal combinations of short-term activities. The constraints on the short-term activities that, if satisfied, lead to the recognition of a long-term activity, are expressed using a dialect of the Event Calculus. We illustrate the expressiveness of the dialect by showing the representation of several typical complex activities. Furthermore, we present a detailed evaluation of the system through experimentation on a benchmark dataset of surveillance videos.
- J. Allen and G. Ferguson. Actions and events in interval temporal logic. Journal of Logic and Computation, 4(5):531--579, 1994.Google Scholar
Cross Ref
- A. Artikis and G. Paliouras. Behaviour recognition using the event calculus. In Artificial Intelligence Applications & Innovations. Springer, 2009.Google Scholar
- A. Artikis, A. Skarlatidis, and G. Paliouras. Behaviour recognition from video content using the event calculus. International Journal of AI Tools, 19(2), 2010.Google ScholarCross Ref
- L. Chittaro and A. Montanari. Efficient temporal reasoning in the cached event calculus. Computational Intelligence, 12(3):359--382, 1996.Google ScholarCross Ref
- C. Dousson and P. Le Maigat. Chronicle recognition improvement using temporal focusing and hierarchisation. In IJCAI, pages 324--329, 2007. Google ScholarDigital Library
- C. Fillmore. The case for CASE. In E. Bach and R. Harms, editors, Universals in Linguistic Theory, pages 1--88. Holt, Rinehart, and Winston, 1968.Google Scholar
- A. Hakeem and M. Shah. Learning, detection and representation of multi-agent events in videos. Artificial Intelligence, 171(8--9):586--605, 2007. Google ScholarDigital Library
- D. Kosmopoulos, P. Antonakaki, K. Valasoulis, A. Kesidis, and S. Perantonis. Human behaviour classification using multiple views. In Hellenic Conference on Artificial Intelligence, LNAI 5138. Springer, 2008. Google ScholarDigital Library
- R. Kowalski and M. Sergot. A logic-based calculus of events. New Generation Computing, 4(1):67--96, 1986. Google ScholarDigital Library
- R. Miller and M. Shanahan. The event calculus in a classical logic. JETAI, 4(16), 2000.Google Scholar
- A. Paschke and M. Bichler. Knowledge representation concepts for automated SLA management. Decision Support Systems, 46(1):187--205, 2008. Google ScholarDigital Library
- V. Shet, D. Harwood, and L. Davis. VidMAP: video monitoring of activity with Prolog. In Advanced Video and Signal Based Surveillance. IEEE, 2005.Google Scholar
- V. Shet, J. Neumann, V. Ramesh, and L. Davis. Bilattice-based logical reasoning for human detection. In Computer Vision and Pattern Recognition. IEEE, 2007.Google Scholar
Index Terms
- A logic programming approach to activity recognition
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