1、加载一张图片
main函数：

	cv::Mat img = cv::imread("5.jpg");
	vector<Point2f> points_vec = dectectFace68(img);

2、人脸68特征识别函数

在这里vector<Point2f> dectectFace68(Mat src)
{
	vector<Point2f> points_vec;
	
	int* pResults = NULL;
	//在检测函数中使用了pBuffer。  
	//如果你调用多个线程中的函数，请为每个线程创建一个缓冲区!  
	unsigned char* pBuffer = (unsigned char*)malloc(DETECT_BUFFER_SIZE);
	if (!pBuffer)
	{
		fprintf(stderr, "Can not alloc buffer.\n");
		//return 100;
	}
	Mat gray;
	cvtColor(src, gray, CV_BGR2GRAY);
	int doLandmark = 1;// do landmark detection  
	pResults = facedetect_multiview_reinforce(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step,
		1.2f, 2, 48, 0, doLandmark);

	int cxa = *pResults;

	ofstream file("facedata.txt", ios::out);
	//打印检测结果 



	if (0 == cxa)
	{
	}
	else
	{
		
		for (int i = 0; i < (pResults ? *pResults : 0); i++)
		{
			
			short* p = ((short*)(pResults + 1)) + 142 * i;
			//rectangle(src, Rect(p[0], p[1], p[2], p[3]), Scalar(0, 255, 0), 2);
			if (doLandmark)
			{
				for (int j = 0; j < 68; j++)
				{
					char c[8];
					_itoa(j, c, 10);
					
					

					Point2f ff(p[6 + 2 * j], p[6 + 2 * j + 1]);
					points_vec.push_back(ff);
					file << ff.x << "\t" << ff.y << endl;

				/*	circle(src, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 3, Scalar(0, 0, 255), 3);
					CvPoint font;
					putText(src, c, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(255, 23, 0), 1);*/
					
				}
			}
		}


	

	}



	return points_vec;
}

插入代码片

3、结果