Panoramic Appearance Map (PAM) for Multi-camera Based Person Re-identification

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.