Kinect for windows的脸部识别

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。

结果图像如下图：

 新建一个WinForm项目，在窗体上添加一人ListBox，更改Name为Messbox_LB。后台代码如下：

 

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 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 faceModelPts = new List();

                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 list = new List();
                //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);
                }

            }


            ///
            /// 数据更新的方法
            ///
            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);
                    }
                }
            }

            }
        }
    }
}

 同时项目中需要引入下面文件中的dll。

http://down.51cto.com/data/774502