Detecting pedestrians using patterns of motion and appearance

作者：Viola, Jones, Snow · 年份：2003 · DOI：10.1109/iccv.2003.1238422 · 被引用次数：992 · 研究领域：Video Surveillance and Tracking Methods、Anomaly Detection Techniques and Applications、Human Pose and Action Recognition

This paper describes a pedestrian detection system that integrates image intensity information 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 (using AdaBoost) to take advantage of both motion and appearance information to detect a walking person. Past approaches have built 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 20/spl times/15 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).