Effective scene matching for intelligent video surveillance

Hong Zhang; Xueqing Chen; Ding Yuan; Mingui Sun

doi:10.1117/12.2011051

20 March 2013 Effective scene matching for intelligent video surveillance

Hong Zhang, Xueqing Chen, Ding Yuan, Mingui Sun

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87683A (2013) https://doi.org/10.1117/12.2011051
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

This paper proposes a novel method on scene matching which aims to detect the unauthorized change of the camera’s field of view (FOV) automatically. The problem is substantially difficult due to mixed representation of FOV change and scene content variation in actual situation. In this work, a local viewpoint-invariant descriptor is firstly proposed to measure the appearance similarity of the captured scenes. And then the structural similarity constraint is adopted to further distinguish whether the current scene remains despite the content change in the scene. Experimental results demonstrate that the proposed method works well in existence of viewpoint change, partial occlusion and structural similarities in real environment. The proposed scheme has been proved to be practically applicable and reliable by its use in an actual intelligent surveillance system.

Citation Download Citation

Hong Zhang, Xueqing Chen, Ding Yuan, and Mingui Sun "Effective scene matching for intelligent video surveillance", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87683A (20 March 2013); https://doi.org/10.1117/12.2011051

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