关键词: 方向梯度直方图, 肤色, 发色, 曲率, 弹性模型, 局部二次加权

Abstract: Aiming at the limitations of pedestrian detection using single feature under complex background, this paper proposes an algorithm which fuses several features by using the elastic models and part quadrat-ic weighting. Fusing Histogram of Oriented Gradient（HOG）, skin color, hair color and curvature efficiently, it est-ablishes kinds of feature models which can be adaptive to pedestrian detection. The first level which adopts the improved HOG feature and is combined with elastic models uses the SVM classifier for the first det-ection. The second level extracts the Region Of Interest（ROI） of partial models to detect head skin color, hair color and curvature of the legs. The experimental result shows that the algorithm makes up for the inade-quacy of single feature. Meanwhile, the algorithm detects the whole and part key features of pedestrian effe-ctively and it improves the recognition performance.

Key words: Histogram of Oriented Gradient（HOG）, skin color, hair color, curvature, elastic models, part quadratic weighting