关键词: 行人检测, 金字塔式梯度方向直方图（PHOG）特征, 颜色特征, Adaboost, 线性支持向量机

Abstract: Aiming at real-time deficiency based on histograms of oriented gradient in pedestrian detection, this paper proposes a new method which is based on multi-detector fusion. It uses Adaboost classifier with Haar feature to detect head roughly, however, it exists some undetected cases in the process because of the pedestrian poses or dimension problems in the images. It adopts Canny operator to get image contour and obtains image contour based on color feature, then it extracts the possible detective area in the image by using ellipse fitting. According to the previous rough detection results and through suitably changing the scale of candidate region, it gets PHOG feature and judges by using linear SVM. It is approved that the new method is efficient and available in the test of INRIA sample database.

Key words: pedestrian detection, Pyramid of Histograms of Oriented Gradient（PHOG） feature, color feature, Adaboost, linear Support Vector Machine（SVM）