International Journal of Computer Vision

, Volume 63, Issue 2, pp 153–161

Detecting Pedestrians Using Patterns of Motion and Appearance

Article

Abstract

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).

Keywords

pedestrian detection human sensing boosting tracking 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Microsoft ResearchOne Microsoft WayRedmondUSA
  2. 2.Mitsubishi Electric Research LaboratoriesCambridgeUSA

Personalised recommendations