直接上代码

            FrameSource cameraSource = FrameSource.CreateFrameSource_Camera(0);

            while (true)
            {
                Mat frame = new Mat();
                CascadeClassifier faceCascade = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
                float scalingFactor = 0.75f;

                cameraSource.NextFrame(frame);
                Cv2.Resize(frame, frame, new Size(), scalingFactor, scalingFactor, InterpolationFlags.Area);
                Mat frameGray = frame.CvtColor(ColorConversionCodes.BGR2GRAY);
                frameGray = frameGray.EqualizeHist();// 均衡直方图，防止太亮或太暗，影响检测效果

                Rect[] faces = faceCascade.DetectMultiScale(frameGray, 1.1, 2, HaarDetectionType.ScaleImage, new Size(30, 30));

                Mat result = frameGray.Clone();
                foreach (Rect face in faces)
                {
                    var center = new Point
                    {
                        X = (int)(face.X + face.Width * 0.5),
                        Y = (int)(face.Y + face.Height * 0.5)
                    };
                    var axes = new Size
                    {
                        Width = (int)(face.Width * 0.5),
                        Height = (int)(face.Height * 0.5)
                    };
                    Cv2.Ellipse(result, center, axes, 0, 0, 360, new Scalar(255, 0, 255), 4);
                }

                Cv2.ImShow("Faces by Haar", result);
                Cv2.WaitKey(20);
            }

非常简单，直接使用前人训练出来的模型进行detect即可。

至于haar模型的训练，参见
https://blog.csdn.net/sazass/article/details/93073840