Joint moving cast shadows segmentation and light source detection in video sequences

Abstract

This paper proposes a new method which allows a joint estimation of the light source projection on the image plane and the segmentation of moving cast shadows in natural video sequences. It allows improving the segmentation of moving objects by separating clearly cast shadows from moving objects. The method is based on a shadow model which mainly assumes that the cast shadows are projected on plane and Lambertian surfaces, and that the light source is unique. The moving cast shadows, including the penumbra, are detected using a segmentation method based on a comparison between a reference image and the original one. The light source position is estimated using geometrical relations linking the light source, the object and its cast shadow on the 2-D image plane. This is obtained using a robust temporal filtering method. For each image using the current estimation of the light source position and the video object contours, a cast shadow search area is defined. This reduces the risk of false detections during the segmentation process, and thus allows increasing the detection rate and reducing the false alarm one. Experimental results show that good shadow and object contours and light source locations are obtained with the proposed method even if the theoretical assumptions are not fully valid.