Moving object detection unaffected by cast shadows, highlights and ghosts

This paper describes a new approach to perform segmentation of moving objects in real-time from images acquired by a fixed color video camera and is the first tool of a major project that aspires to recognize abnormal human behavior in public areas. The moving objects detection is based on background subtraction and it is unaffected by changes in illumination, i.e., cast shadows and highlights. Furthermore it does not require a special attention during the initialization process, due to its ability to detect and rectify ghosts. The results show that with image resolutions of 380×280 at 24 bits per pixel, the time spent in the segmentation process is around 80 ms, in a 32 bits 3 GHz processor based computer.