Exploitation of multi-camera configurations for visual surveillance

Date

2008-06-20

Author

Akman, Oytun
Alatan, Abdullah Aydın
Çiloğlu, Tolga

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper, we propose novel methods for background modeling, occlusion. handling and event recognition by using multi-camera configurations. Homography-related positions are utilized to construct a mixture of multivariate Gaussians to generate a background model for each pixel of the reference camera. Occlusion handling is achieved by generation of the top-view via trifocal tensors, as a result of matching over-segmented regions instead of pixels. The resulting graph is segmented into objects after determining the minimum spanning tree of this graph. Tracking of multiview data is obtained by utilizing measurements across the views in case of occlusions. Finally, the resulting trajectories are classified by GM-HMMs, yielding better results for using all different trajectories of the same object together.

Subject Keywords

Surveillance, Cameras , Gaussian processes, Layout , Object detection, Trajectory , Tensile stress, Costs , Lighting , Tree graphs

URI

https://hdl.handle.net/11511/49126

DOI

https://doi.org/10.1109/cbmi.2008.4564939

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

O. Akman, A. A. Alatan, and T. Çiloğlu, “Exploitation of multi-camera configurations for visual surveillance,” 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/49126.