Detecting Pedestrians Using Patterns of Motion and Appearance

• Published in: International journal of computer vision 2005-07, Vol.63 (2), p.153-161
• Main Authors: Viola, Paul, Jones, Michael J, Snow, Daniel
• Format: Article
• Language: English
• Subjects: Pedestrians; Sensors
• ISSN: 0920-5691; 1573-1405
• DOI: 10.1007/s11263-005-6644-8

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 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 20 × 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).[PUBLICATION ABSTRACT]