Citation

Dai C, Zheng Y, Li X. Comput. Vis. Image Underst. 2007; 106(2-3): 288-299.

Copyright

(Copyright © 2007, Elsevier Publishing)

DOI

10.1016/j.cviu.2006.08.009

PMID

unavailable

Abstract

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appear- ance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to sep- arate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multi- ple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance informa- tion. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.