Two-Phased Region Integration Approach for Effective Pedestrian Detection in Low Contrast Images

Abstract

An accurate pedestrian detection method is proposed, which is effective especially in low-contrast images. The pedestrian detection method generally consists of two serial functions: one is moving object extraction, and the other is pedestrian decision. In particular, the moving objects need to be extracted precisely for the accurate pedestrian detection. However, since the moving objects are extracted as multiple small regions when the image contrast is low, the pedestrian detection often fails. To overcome this problem, the proposed method integrates the separated moving objects by two-phased region integration. In the first phase, the pieces of the moving objects are integrated by applying the watershed algorithm. Then, these regions are, in the second phase, further integrated by watching the outputs of support vector machines for the pedestrian detection. By using these integration schemes, the moving objects are appropriately extracted, and thereby the accurate pedestrian detection can be realized.