Automatic Annotation of Humans in Surveillance Video

In this paper we present a system for automatic annotation of humans passing a surveillance camera. Each human has 4 associated annotations: the primary color of the clothing, the height, and focus of attention. The annotation occurs after robust background subtraction based on a Codebook representation. The primary colors of the clothing are estimated by grouping similar pixels according to a body model. The height is estimated based on a 3D mapping using the head and feet. Lastly, the focus of attention is defined as the overall direction of the head, which is estimated using changes in intensity at four different positions. Results show successful detection and hence successful annotation for most test sequences.