People re-identification by graph kernels methods
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
A graph-kernel method for re-identification
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
SARC3D: a new 3D body model for people tracking and re-identification
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
3DPeS: 3D people dataset for surveillance and forensics
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
Fast person re-identification based on dissimilarity representations
Pattern Recognition Letters
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
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This paper proposes a concept of panoramic appearance map to perform reidentification of a people who leave the scene and reappear after some time. The map is a compact signature of appearance information of a person extracted from multiple cameras. The person is detected and tracked in multiple cameras and triangulation is used to accurately localize the person in 3-D. A virtual cylinder is formed around the person's location and mapped onto an image with the horizontal axis representing the azimuth angle and vertical axis representing the height. Each bin in the map image gets the appearance information from all the cameras which can observe it. The maps between different tracks are matched using a weighted metric. Experimental results showing person matching and reidentification show the effectiveness of the approach.