Abstract
In this paper we fully develop a fall detection application that focuses on complex event detection. We use a decoupled approach, whereby the definition of events and of their complexity is fully detached from low and intermediate image processing level. We focus on context independence and flexibility to allow the reuse of existing approaches on recognition task. We build on existing proposals based on domain knowledge representation through ontologies. We encode knowledge at the rule level, thus providing a more flexible way to handle complexity of events involving more actors and rich time relationships. We obtained positive results from an experimental dataset of 22 recordings, including simple and complex fall events.
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Turaga, P., Chellappa, R., Subrahmaniam, V.S., Udrea, O.: Machine Recognition of Human Activities: A survey. IEEE Transactions on Circuits and Systems for Video Technology 18, 1473–1488 (2008)
Poppe, R.: A survey on vision-based human action recognition. Image and Vision Computing 28(6), 976–990 (2010)
Francois, A.R., Nevatia, R., Hobbs, J., Bolles, R.C., Smith, J.: VERL: an ontology framework for representing and annotating video events. IEEE MultiMedia Magazine 12(4), 76–86 (2005)
Snidaro, L., Belluz, M., Foresti, G.L.: Representing and recognizing complex events in surveillance applications. In: Proc. of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, pp. 493–498 (2007)
Snidaro, L., Belluz, M., Foresti, G.L.: Modelling and Managing Domain Context for Automatic Surveillance Systems. In: Sixth IEEE International Conference on Advanced Video and Signal ased Surveillance (AVSS), pp. 238–243 (2009)
Rougier, C., Meunier, J., St-Arnaud, A., Rousseau, J.: Fall Detection from Human Shape and Motion History Using Video Surveillance. In: Proc. of the 21st International Conference on Advanced Information Networking and Applications Workshops, pp. 875–880 (2007)
Kim, K., Chalidabhongse, T., Harwood, D., Davis, L.: Real-time foreground-background segmentation using codebook model. Real-Time Imaging 11(3), 172–185 (2005)
Chaudhuri, B.B., Samanta, G.P.: Elliptic fit of objects in two and three dimensions by moment of inertia optimization. Pattern Recognition Letters 12(1), 1–7 (1991)
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Bartocci, D., Ferretti, M. (2011). Handling Complex Events in Surveillance Tasks. In: Maino, G., Foresti, G.L. (eds) Image Analysis and Processing – ICIAP 2011. ICIAP 2011. Lecture Notes in Computer Science, vol 6979. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24088-1_11
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DOI: https://doi.org/10.1007/978-3-642-24088-1_11
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