Abstract
Pedestrian detection from a video sequence is a challenging problem. In this paper, we mainly use active basis model which consists of a small number of Gabor wavelet elements at selected locations and orientations to detect pedestrian. In order to enhance the detection rate, we propose an adaptive background modeling method for background subtraction method to detect objects in video sequence which emphasize background and remove foreground using mask technology. After acquiring many pedestrian templates of different poses and orientations, active basis method can be applied in pose estimation and human action analysis. The detection results indicate that our approach is capable of obtaining better detecting effects and pose estimation even under conditions of noise and illumination changes.
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