Moving Cast Shadow Detection by Energy Minimization

Moving cast shadow causes serious problem while segmenting and extracting true foreground from image sequences, due to the misclassification of moving shadow as foreground. This paper proposes a novel approach for moving cast shadow detection. Firstly, the color and texture information of moving cast shadow is employed with the temporal-spatial coherence of shadow and foreground in a probability framework; afier that, the maximization of posterior probability can be converted to energy minimization problem through Gibbs energy; finally, moving cast shadow and foreground can be segmented accurately through graph cut. Results show that the proposed method excels classical method both in indoor and outdoor scene.