在智能视频监控领域，行人检测正受到广泛关注。为了提高检测率，将基于局部特征的Adaboost级联分类器和模板匹配相结合。首先通过分析和比较提出了一种行人局部特征的选取方法，然后对人体局部进行建模，将模板匹配的思想融入行人检测。最后通过实验证明，该方法在行人检测上可以取得较好的效果。

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.