基于多特征的AdaBoost行人检测算法, 提出一种融合灰

度和轮廓信息的新的多特征综合表示方法. 该方法通过统计样本的权重直方图建立分类模

型, 并用多个直方图的乘积表示样本在多特征下对应的联合概率分布-AdaBoost pedestrian detection algorithm based on multi-feature, presents a fusion of grayscale and contour information of the new multi-feature comprehensive representation of this method through the right to establish a statistical sample of heavy histogram classification model, and the product of said plurality of samples in a histogram multi-joint probability distribution corresponding characteristics