This paper presents a pedestrian detection framework using a top-view camera. The paper contains two novel contributions for the pedestrian detection task: 1. Using shape context method to estimate the pedestrian directions and normalizing the pedestrian regions. 2. Based on the locations of the extracted head candidates, system chooses the most adaptive classifier from several classifiers automatically. Our proposed methods may solve the difficulties on top-view pedestrian detection field. Experimental was performed on video sequences with different illumination and crowed conditions, the experimental results demonstrate the efficiency of our algorithm.