Accord.NET代替：VisioForge .Net SDKへの移行ガイド

var videoDevices = new FilterInfoCollection(FilterCategory.VideoInputDevice);
var videoSource = new VideoCaptureDevice(videoDevices[0].MonikerString);
videoSource.NewFrame += (s, e) =>
{
    pictureBox.Image = (Bitmap)e.Frame.Clone();
};
videoSource.Start();

var capture = new VideoCaptureCoreX(videoView);
var devices = await DeviceEnumerator.Shared.VideoSourcesAsync();
capture.Video_Source = new VideoCaptureDeviceSourceSettings(devices[0]);
capture.Outputs_Add(new MP4Output("recording.mp4"), true);
await capture.StartAsync();

var detector = new HaarObjectDetector(
    new HaarCascade(HaarCascade.FaceHaarCascadePath));
detector.MinSize = new Size(30, 30);
Rectangle[] faces = detector.ProcessFrame(bitmap);

var settings = new CVFaceDetectSettings
{
    DetectFrontalFace = true,
    DetectEyes = true,
    DetectNose = true,
    DetectMouth = true,
    MinFaceSize = new Size(30, 30),
    ScaleFactor = 1.1,
    DrawEnabled = true
};
var detector = new CVFaceDetectBlock(settings);
// Add to a MediaBlocks pipeline or use standalone

var hog = new HistogramsOfOrientedGradients();
double[] features = hog.ProcessImage(bitmap);
// Manual SVM classification needed

var settings = new CVFaceDetectSettings
{
    DrawEnabled = true,
    VideoScale = 1.0,
    FramesToSkip = 2
};
var detector = new CVFaceDetectBlock(settings);

var detector = new MotionDetector(
    new TwoFramesDifferenceDetector(),
    new BlobCountingObjectsProcessing());
double motionLevel = detector.ProcessFrame(bitmap);

var settings = new CVMotionCellsSettings
{
    DrawEnabled = true
};
var detector = new CVMotionCellsBlock(settings);
// MOG2 background subtraction with automatic object tracking and ID assignment