说明：  方向梯度直方图（Histogram of Oriented Gradient, HOG）特征是一种在计算机视觉和图像处理中用来进行物体检测的特征描述子。它通过计算和统计图像局部区域的梯度方向直方图来构成特征。Hog特征结合SVM分类器已经被广泛应用于图像识别中，尤其在行人检测中获得了极大的成功。需要提醒的是，HOG+SVM进行行人检测的方法是法国研究人员Dalal在2005的CVPR上提出的，而如今虽然有很多行人检测算法不断提出，但基本都是以HOG+SVM的思路为主
(The Histogram of Oriented Gradient (HOG) feature is a feature descriptor for object detection in computer vision and image processing. It constructs features by computing and counting histograms of gradient directions in local regions of images. Hog features and SVM classifier have been widely used in image recognition, especially in pedestrian detection. It needs to be reminded that the method of pedestrian detection by HOG+SVM is proposed by French researcher Dalal on 2005 of CVPR, and although many pedestrian detection algorithms are constantly proposed, it is mainly based on the idea of HOG+SVM.)