为了快速准确地对行人进行检测，提出了一种采用空间梯度直方图作为特征的行人检测方法。该方法首先使用直方图相似性和Fisher准则来衡量所有定义特征的分辨能力，然后选择一些具有强分辨能力的特征来表征行人，使该方法获得了较高的检测率；最后用SVM分类器用来训练从目标和背景中获得的经过筛选的特征。实验结果表明，该方法对行人的检测是快速且有效的。

This paper presents a pedestrian detection approach using spatial histograms of oriented gradient feature. In order to detect pedestrians faster and more accurately, histogram similarity and Fisher criterion are employed to measure discriminability of all features and then we selected some discriminative features to identify the pedestrian. SVM classifier is constructed to train the selected features from the target and surrounding background. Experimental results show that the proposed approach is efficient and rapid in pedestrian detection.