Abstract
This paper is about tracking people in real-time as they move through the non-overlapping fields of view of multiple video cameras. The paper builds upon existing methods for tracking moving objects in a single camera. The key extension is the use of a stochastic transition matrix to describe people’s observed patterns of motion both within and between fields of view. The parameters of the model for a particular environment are learnt simply by observing a person moving about in that environment. No knowledge of the environment or the configuration of the cameras is required.
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Dick, A.R., Brooks, M.J. (2004). A Stochastic Approach to Tracking Objects Across Multiple Cameras. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_15
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DOI: https://doi.org/10.1007/978-3-540-30549-1_15
Publisher Name: Springer, Berlin, Heidelberg
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