Kinect for windows的脸部识别-阿里云开发者社区

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<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);
}
}
}
}
}
}
}

同时项目中需要引入下面文件中的dll。

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

本文转自桂素伟51CTO博客，原文链接：http://blog.51cto.com/axzxs/1191261 ，如需转载请自行联系原作者

Kinect for windows的脸部识别

热门文章

最新文章

相关电子书

相关实验场景