Towards detection of moving cast shadows for visual traffic surveillance

In this paper, an effective method for the detection of moving cast shadow for visual traffic surveillance is proposed. Based on the cast shadow observations in luminance, chrominance, gradient density and geometry domains, a combined probability map, called the shadow confidence score, of the region belonging to the shadow is deduced. The object region is then separated from its shadow according to the score. The proposed method has been further tested on images taken under different lighting conditions (sunny and cloudy), viewing angles (roadside and overhead), and vehicle sizes (small, medium and large).