OpenCV计算机视觉编程攻略之行人检测，OpenCV 提供了一个基于HOG 和SVM且经过训练的行人检测器，可以用这个SVM 分类器以不同尺度的窗口扫描图像，在完整的图像中检测特定物体。

原图如下：

检测效果图如下：

源码如下：

#include <opencv2/opencv.hpp>

int main()
{
	// People detection
	cv::Mat myImage = imread("demo.jpg", cv::IMREAD_GRAYSCALE);

	// create the detector
	std::vector<cv::Rect> peoples;
	cv::HOGDescriptor peopleHog;
	peopleHog.setSVMDetector(cv::HOGDescriptor::getDefaultPeopleDetector());
	// detect peoples oin an image
	peopleHog.detectMultiScale(myImage, // input image
		peoples, // ouput list of bounding boxes 
		0,       // threshold to consider a detection to be positive 
		cv::Size(4, 4),   // window stride 
		cv::Size(32, 32), // image padding
		1.05,              // scale factor
		2);               // grouping threshold (0 means no grouping) 

	// draw detections on image
	std::cout << "Number of peoples detected: " << peoples.size() << std::endl;
	for (int i = 0; i < peoples.size(); i++)
		cv::rectangle(myImage, peoples[i], cv::Scalar(255, 255, 255), 2);

	cv::imshow("People detection", myImage);

	cv::waitKey();
	return 0;
}