Pedestrian detection based on appearance, motion, and shadow information

We present a new pedestrian detection algorithm that considers multiple information sources. Appearance-based detection methods face difficulties such as appearance variations and occlusions. Shape-based methods can have false positives on shadows since they usually have similar shapes with foreground objects. To deal with these problems, we use appearance, motion, and shadow information simultaneously in our detection method. We detect pedestrians using shape information of both foreground and shadow regions. Then, we filter the detection results based on motion information if available. The proposed method gives low false positives due to the integration of multiple information sources. Moreover, it alleviates the problem brought by occlusion since casted shadows are observable when foreground objects are occluded. Our experimental results show that the proposed algorithm provides good performance in difficult situations.