Detecting Pedestrians Using Patterns of Motion and Appearance-英文文献.pdf

MITSUBISHI ELECTRIC RESEARCH LABORATORIES Detecting Pedestrians Using Patterns of Motion and Appearance Paul Viola Michael Jones Daniel Snow TR2003-90 July 2003 Abstract This paper describes a pedestrian detection system that integrates image intensity in- formation with motion information. We use a detection style algorithm that scans a detector over two consecutive frames of a video sequence. The detector is trained (us- ing AdaBoost) to take advantage of both motion and appearance information to detect a walking person. Past approaches have built detectors based on motion information or detectors based on appearance information, but ours is the first to combine both sources of information in a single detector. The implementation described runs at about 4 frames/second, detects pedestrians at very small scales (as small as 20x15 pixels), and has a very low false positive rate. Our approach builds on the detection work of Viola and Jones. Novel contributions of this paper include: i) development of a representation of image motion which is extremely efficient, and ii) implementation of a state of the art pedestrian detection system which operates on low resolution images under difficult conditions (such as rain and snow). To appear in the Proceedings of the International Conference on Computer Vision (ICCV), October 13, 2003, Nice, France. This work m