Multicamera object detection and tracking with object size estimation

A number of multi-camera solutions exist for tracking objects of interest in surveillance scenes. Generally, the approach follows the idea of either early fusion (where all cameras are used to make a decision about detection and tracking) or late fusion (where objects are detected and tracked in individual cameras independently, and then the results combined). This paper describes an early fusion approach derived from the common approach of projecting foreground mask into a common coordinate system. The described approach extends prior work to suppress false detections and automatically estimate the size of the object under tracking, thus enabling it to work in environments containing a mix of people and vehicles.