In a typical video surveillance framework, a single camera or a set of cameras monitor a scene in which human activities are carried out. In this paper, we propose a complementary framework where human activities can be analyzed under a subjective point of view. The idea is to represent the focus of attention of a person in the form of a 3D view frustum, and to insert it in a 3D representation of the scene. This leads to novel inferences and reasoning on the scene and the people acting in it. As a particular application of this proposed framework, we collect the information from the subjective view frusta in an Interest Map, i.e. a map that gathers in an effective and intuitive way which parts of the scene are observed more often in a defined time interval. The experimental results on standard benchmark data witness the goodness of the proposed framework, encouraging further efforts for the development of novel applications in the same direction. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Farenzena, M., Bazzani, L., Murino, V., & Cristani, M. (2009). Towards a subject-centered analysis for automated video surveillance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 481–489). https://doi.org/10.1007/978-3-642-04146-4_52
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