Kinect for windows的脸部识别

需要引入的dll：

需要将下面两个dll复制到当前路径

Kinect for windows提供了脸部识别的功能，可以识出人脸。主要是通过FaceTrackFrame类的GetTriangles()来得到一个三角形数组，这个三角形数组就是给成人面部的基本形状，并且组成的效果是立体的（可以这样理解，可以把3D都拆成三角形来表示，看上去像3D，但其实是2D），这个数组的每个元素都存放着三个整数，分别代码三角形的第一个点，第二个点和第三个点。FaceTrackFrame的GetProjected3DShape方法，可以获取一组坐标信息，这样就可以结合三角形数组元素中的点作为索引，从本方法的坐标集合中取出每个三角形的坐标点来了，就可以绘制这些三角形，就可以组成一个人脸的网络3D效果图了。

本例是从色彩摄像头中获取彩色数据流，并显示到窗体上，再通过FaceTracker得到得到脸部3D信息，并用GDI+的方式把网络图形画到窗体上，这时就可以在真实图像上看到浮着一张网络的面套。同时可以得出脸部交汇最多的坐标，并用GDI+添加上不同有色彩，同时还可以得到人体面部和Kinect 正面的偏差，即人头是否竖直，有没有偏上一边等角度信息。

using System;  using System.Collections.Generic;  using System.ComponentModel;  using System.Data;  using System.Drawing;  using System.Linq;  using System.Text;  using System.Threading.Tasks;  using System.Windows.Forms;   using Microsoft.Kinect;  using Microsoft.Kinect.Toolkit;  using Microsoft.Kinect.Toolkit.FaceTracking;  using System.Threading;  using System.IO;  using System.Drawing.Imaging;    namespace Face  {      public partial class Form1 : Form      {          public Form1()          {              InitializeComponent();          }           KinectSensor ks = null;          private void Form1_Load(object sender, EventArgs e)          {              //让winform窗体刷新不闪动              this.SetStyle(ControlStyles.OptimizedDoubleBuffer, true);              this.SetStyle(ControlStyles.AllPaintingInWmPaint, true);              this.SetStyle(ControlStyles.UserPaint, true);              this.SetStyle(ControlStyles.DoubleBuffer, true);              //找到连接的Kinect设备              foreach (var ks in KinectSensor.KinectSensors)              {                  if (ks.Status == KinectStatus.Connected)                  {                      this.ks = ks;                  }              }              //开启色彩流，深度流，骨骼流的跟踪              if (this.ks != null)              {                  this.ks.ColorStream.Enable(ColorImageFormat.RgbResolution640x480Fps30);                  this.ks.DepthStream.Enable(DepthImageFormat.Resolution320x240Fps30);                  this.ks.DepthStream.Range = DepthRange.Near;                  this.ks.SkeletonStream.EnableTrackingInNearRange = true;                  this.ks.SkeletonStream.TrackingMode = SkeletonTrackingMode.Seated;                  this.ks.SkeletonStream.Enable();                  //订阅跟踪数据读取事件                  this.ks.AllFramesReady += OnAllFramesReady;                  ks.Start();              }          }           //这个方法很重要，就是重绘人脸跟踪采集到的数据          protected override void OnPaint(PaintEventArgs e)          {              base.OnPaint(e);              foreach (SkeletonFaceTracker faceInformation in this.trackedSkeletons.Values)              {                  //第一个参数为当前窗体为画布，第二个是添加采集到的信息到listbox中，这个方法画识别到脸部的信息                  faceInformation.DrawFaceModel(e.Graphics, Messbox_LB);              }          }           //定义脸部识别的集合          private readonly Dictionary<int, SkeletonFaceTracker> trackedSkeletons = new Dictionary<int, SkeletonFaceTracker>();          //色彩流字节数组          private byte[] colorImage;          private ColorImageFormat colorImageFormat = ColorImageFormat.Undefined;          //深度流字节数组          private short[] depthImage;          private DepthImageFormat depthImageFormat = DepthImageFormat.Undefined;          //骨骼信息数组          private Skeleton[] skeletonData;            private void OnAllFramesReady(object sender, AllFramesReadyEventArgs allFramesReadyEventArgs)          {              ColorImageFrame colorImageFrame = null;              DepthImageFrame depthImageFrame = null;              SkeletonFrame skeletonFrame = null;              try             {                  colorImageFrame = allFramesReadyEventArgs.OpenColorImageFrame();     //接到色彩流对框架                  depthImageFrame = allFramesReadyEventArgs.OpenDepthImageFrame();     //接到深度流对框架                  skeletonFrame = allFramesReadyEventArgs.OpenSkeletonFrame();     //接到骨骼流对框架                   if (colorImageFrame == null || depthImageFrame == null || skeletonFrame == null)                  {                      return;                  }                                    if (this.depthImageFormat != depthImageFrame.Format)                  {                      this.ResetFaceTracking();                      this.depthImage = null;                      this.depthImageFormat = depthImageFrame.Format;                  }                   if (this.colorImageFormat != colorImageFrame.Format)                  {                      this.ResetFaceTracking();                      this.colorImage = null;                      this.colorImageFormat = colorImageFrame.Format;                  }                  if (this.depthImage == null)                  {                      this.depthImage = new short[depthImageFrame.PixelDataLength];                  }                   if (this.colorImage == null)                  {                      this.colorImage = new byte[colorImageFrame.PixelDataLength];                  }                   if (this.skeletonData == null || this.skeletonData.Length != skeletonFrame.SkeletonArrayLength)                  {                      this.skeletonData = new Skeleton[skeletonFrame.SkeletonArrayLength];                  }                  //获取各种数据流信息                  colorImageFrame.CopyPixelDataTo(this.colorImage);                  depthImageFrame.CopyPixelDataTo(this.depthImage);                  skeletonFrame.CopySkeletonDataTo(this.skeletonData);                  //清空列表信息                  Messbox_LB.Items.Clear();                  //编历骨骼流                  foreach (Skeleton skeleton in this.skeletonData)                  {                      //找到有效的骨骼信息                      if (skeleton.TrackingState == SkeletonTrackingState.Tracked                          || skeleton.TrackingState == SkeletonTrackingState.PositionOnly)                      {                          if (!this.trackedSkeletons.ContainsKey(skeleton.TrackingId))                          {                              //添加骨骼信息到集合中                              this.trackedSkeletons.Add(skeleton.TrackingId, new SkeletonFaceTracker());                          }                          // 得到脸部识别对象                          SkeletonFaceTracker skeletonFaceTracker;                          if (this.trackedSkeletons.TryGetValue(skeleton.TrackingId, out skeletonFaceTracker))                          {                              //把获取的数据流的相关信息传给OnFrameReady方法                              skeletonFaceTracker.OnFrameReady(Messbox_LB, this.ks, colorImageFormat, colorImage, depthImageFormat, depthImage, skeleton);                              skeletonFaceTracker.LastTrackedFrame = skeletonFrame.FrameNumber;                          }                      }                  }                  //这个刷新会触发窗体的重画，OnPaint方法会被调用。                  this.Refresh();                  //把色彩流转转成位图显示成窗体的背景                  this.BackgroundImage = ToGrayBitmap(colorImage, 640, 480);               }              finally             {                  if (colorImageFrame != null)                  {                      colorImageFrame.Dispose();                  }                  if (depthImageFrame != null)                  {                      depthImageFrame.Dispose();                  }                  if (skeletonFrame != null)                  {                      skeletonFrame.Dispose();                  }              }          }          //把色采流数据转成位图返回          public static Bitmap ToGrayBitmap(byte[] rawValues, int width, int height)          {              //定议转换图片的格式，一个像素占32个，前24位为红绿蓝，后8位为空              PixelFormat pf = PixelFormat.Format32bppRgb;              //申请目标位图的变量              Bitmap bmp = new Bitmap(width, height, pf);              //将其内存区域锁定               BitmapData bmpData = bmp.LockBits(new Rectangle(0, 0, width, height), ImageLockMode.WriteOnly, pf);              //获取位图的起始地址              IntPtr iptr = bmpData.Scan0;              //用Marshal的Copy方法，将色彩流字节数组复制到BitmapData中               System.Runtime.InteropServices.Marshal.Copy(rawValues, 0, iptr, rawValues.Length);              //释放锁              bmp.UnlockBits(bmpData);              return bmp;          }          //重新设置识别对象          private void ResetFaceTracking()          {              foreach (int trackingId in new List<int>(this.trackedSkeletons.Keys))              {                  this.RemoveTracker(trackingId);              }          }          //从集合中移动识别信息          private void RemoveTracker(int trackingId)          {              this.trackedSkeletons[trackingId].Dispose();              this.trackedSkeletons.Remove(trackingId);          }           private void Form1_FormClosing(object sender, FormClosingEventArgs e)          {              if (this.ks.Status == KinectStatus.Connected)              {                  ks.Stop();              }          }          //定义脸识别类          class SkeletonFaceTracker : IDisposable          {              //定义脸部识别形状三角形数组              private static FaceTriangle[] faceTriangles;              //脸部识别坐标点集合              private EnumIndexableCollection<FeaturePoint, Microsoft.Kinect.Toolkit.FaceTracking.PointF> facePoints;              //脸部跟踪类              private FaceTracker faceTracker;              //定义识别成功标识              private bool lastFaceTrackSucceeded;              //骨骼跟踪状态              private SkeletonTrackingState skeletonTrackingState;               public int LastTrackedFrame { get; set; }               public void Dispose()              {                  if (this.faceTracker != null)                  {                      this.faceTracker.Dispose();                      this.faceTracker = null;                  }              }              //用来把识别的信息绘制出来              public void DrawFaceModel(Graphics graphics, ListBox lb)              {                  if (!this.lastFaceTrackSucceeded || this.skeletonTrackingState != SkeletonTrackingState.Tracked)                  {                      return;                  }                   List<System.Drawing.PointF> faceModelPts = new List<System.Drawing.PointF>();                   for (int i = 0; i < this.facePoints.Count; i++)                  {                      faceModelPts.Add(new System.Drawing.PointF(this.facePoints[i].X + 0.5f, this.facePoints[i].Y + 0.5f));                  }                  System.Drawing.Pen pen = new System.Drawing.Pen(System.Drawing.Color.Green);                   List<System.Drawing.PointF> list = new List<System.Drawing.PointF>();                  //遍历所有的三角形，分别画三角形                  for (int i = 0; i < faceTriangles.Count(); i++)                  {                      System.Drawing.PointF[] pointFarr = new System.Drawing.PointF[4];                      pointFarr[0] = faceModelPts[faceTriangles[i].First];                      pointFarr[1] = faceModelPts[faceTriangles[i].Second];                      pointFarr[2] = faceModelPts[faceTriangles[i].Third];                      pointFarr[3] = faceModelPts[faceTriangles[i].First];                      list.AddRange(pointFarr.Take(3));                      graphics.DrawLines(pen, pointFarr);                  }                   lb.Items.Add(list.GroupBy(f => f).Count() + "点");                  int count = list.GroupBy(f => f).Max(s => s.Count());                  lb.Items.Add(count);                  foreach (var v in list.GroupBy(f => f).Where(s => s.Count() == 10))                  {                      lb.Items.Add(v.Key + " " + 10);                      graphics.FillEllipse(new SolidBrush(System.Drawing.Color.Red), v.Key.X, v.Key.Y, 5, 5);                  }                  foreach (var v in list.GroupBy(f => f).Where(s => s.Count() == 9))                  {                      lb.Items.Add(v.Key + " " + 9);                      graphics.FillEllipse(new SolidBrush(System.Drawing.Color.Blue), v.Key.X, v.Key.Y, 5, 5);                  }                  foreach (var v in list.GroupBy(f => f).Where(s => s.Count() == 8))                  {                      lb.Items.Add(v.Key + " " + 8);                      graphics.FillEllipse(new SolidBrush(System.Drawing.Color.Black), v.Key.X, v.Key.Y, 5, 5);                  }               }                /// <summary>              /// 数据更新的方法              /// </summary>              internal void OnFrameReady(ListBox lb, KinectSensor kinectSensor, ColorImageFormat colorImageFormat, byte[] colorImage, DepthImageFormat depthImageFormat, short[] depthImage, Skeleton skeletonOfInterest)              {                  this.skeletonTrackingState = skeletonOfInterest.TrackingState;                  //判断是否为跟踪状态                  if (this.skeletonTrackingState != SkeletonTrackingState.Tracked)                  {                      return;                  }                  if (this.faceTracker == null)                  {                      try                     {                          //从KinectSensor中实例化出一个脸部识别对象                          this.faceTracker = new FaceTracker(kinectSensor);                      }                      catch (InvalidOperationException)                      {                          this.faceTracker = null;                      }                  }                   if (this.faceTracker != null)                  {                      //从脸部识别对象中得到脸识别框架                      FaceTrackFrame frame = this.faceTracker.Track(                          colorImageFormat, colorImage, depthImageFormat, depthImage, skeletonOfInterest);                      //标识识别成功                      this.lastFaceTrackSucceeded = frame.TrackSuccessful;                      if (this.lastFaceTrackSucceeded)                      {                          if (faceTriangles == null)                          {                              //得到脸部识别三角形数组                              faceTriangles = frame.GetTriangles();                                                       }                          //得到脸部识别点的坐标                          this.facePoints = frame.GetProjected3DShape();                           //加载脸部的空间位置                           lb.Items.Add("Rotation   仰低头:" + frame.Rotation.X);                          lb.Items.Add("Rotation   左右转头:" + frame.Rotation.Y);                          lb.Items.Add("Rotation   左右偏头:" + frame.Rotation.Z);                      }                  }              }                           }          }      }  }