Pedestrian Detection Based on Partial Feature and Model Matching
基于局部特征级联分类器和模板匹配的行人检测

In the field of intelligence video surveillance, pedestrian detection is paid great attention to the security of daily life. In order to raise the detection rate, we combine partial features based on Adaboost with model matching. First, a new way of selecting proper partial feature is shown through analysis and comparison. Then, partial body is used in modeling which shows that model matching is combined in pedestrian detection. At last, experiments indicate that our method achieves a good result in pedestrian detection.