Foreground and Shadow Segmentation by Exploiting Multiple Cues

To segment foreground objects and moving shadows in visual surveillance environment, this paper proposes an algorithm by exploiting color information, illumination invariants and spatial information. The presence of a shadow is first hypothesized with simple evidence that shadows darken the surface which they are cast upon. Derivatives of illumination invariants are then used to classify the potential shadow pixels extracted in previous step. To increase the accuracy of shadow detection, two types of spatial analysis are designed to verify actual shadow pixels. Experimental results show that the proposed algorithm can detect moving shadow effectively on indoor and outdoor video sequences. The performance of the method is considerably higher than that of the two well-known shadow detection methods, and it is robust against changing illumination.