kinect学习笔记（四）——各种数据流

一、kinect开发的一个流程图

1、我们可以知道一个简单的框架就是几部分

（1）选择使用的kinect传感器

KinectSensor.KinectSensors[0]

（2）打开需要的数据流

_kinect.DepthStream.Enable();
_kinect.ColorStream.Enable();
_kinect.SkeletonStream.Enable();

（3）注册事件

其实就是主要的算法在这里体现。

有个小窍门：VS的CodeSnippet快速生成事件代码，如在代码“_kinect.DepthFrameReady+=”后面连续按两次“Tab”键，就会生成相应的时间并处理相应的代码。

二、初始化、启用kinect设备

代码如下，记得要声明一个私有成员变量_kinect，并在MainWindow()里面调用。

KinectSensor _kinect;

        private void startKinect()
        {
            if(KinectSensor.KinectSensors.Count>0)
            {
                //选择第一个kinect设备
                _kinect = KinectSensor.KinectSensors[0];
                MessageBox.Show("Kinect目前状态为：" + _kinect.Status);

                //初始化设定，启用彩色图像，深度图像和骨骼追踪
                _kinect.ColorStream.Enable(ColorImageFormat.RgbResolution640x480Fps30);
                _kinect.DepthStream.Enable(DepthImageFormat.Resolution640x480Fps30);
                _kinect.SkeletonStream.Enable();

                //注册时间，该方法将保证彩色图像，深度图像和骨骼图像的同步
                _kinect.AllFramesReady += _kinect_AllFramesReady;

                //启动kinect
                _kinect.Start();
            }
            else
            {
                MessageBox.Show("没有发现任何kinect设备");
            }
        }

void _kinect_AllFramesReady(object sender, AllFramesReadyEventArgs e)
{
            
}

三、彩色图像流数据处理

1、在MainWindows窗体上新增一个Image控件，命名为imageCamera

2、在_kinect_AllFramesReady事件处理中增加如下代码、

//显示彩色摄像头
           using(ColorImageFrame colorFrame = e.OpenColorImageFrame())
           {
               if(colorFrame == null)
               {
                   return;
               }

               byte[] pixels = new byte[colorFrame.PixelDataLength];
               colorFrame.CopyPixelDataTo(pixels);

               //BGR32格式图片一个像素为4个字节
               int stride = colorFrame.Width * 4;
               ImageCamera.Source = BitmapSource.Create(colorFrame.Width, colorFrame.Height, 96, 96, PixelFormats.Bgr32, null, pixels, stride);

              
           }

      BGR32图像的1像素对应4字节（32位），分别是B,G,R，阿尔法通道（透明度）。

      BitmapSource.Create是一个从数组到二维矩阵的过程。

      Stride为图片步长，代表图片一行像素所占的字节数，为摄像头传输图片的宽度乘以4，

      DPI，越高越清晰，普通的显示器就是96差不多。

3、效果图

四、深度数据捕获

1、定义深度图像的有效视角范围。

const float MaxDepthDistance = 4095;
        const float MinDepthDistance = 850;
        const float MaxDepthDistanceOffest = MaxDepthDistance - MinDepthDistance;

        private const int RedIndex = 2;
        private const int GreenIndex = 1;
        private const int BlueIndex = 0;

2、代码

private byte[]convertDepthFrameToColorFrame(DepthImageFrame depthFrame)
        {
            short[] rawDepthData = new short[depthFrame.PixelDataLength];
            depthFrame.CopyPixelDataTo(rawDepthData);

            Byte[] piexls = new byte[depthFrame.Height * depthFrame.Width * 4];

            for(int depthIndex = 0,colorIndex=0;depthIndex<rawDepthData.Length&&colorIndex<piexls.Length;depthIndex++,colorIndex+=4)
            {
                int player = rawDepthData[depthIndex] & DepthImageFrame.PlayerIndexBitmask;

                int depth = rawDepthData[depthIndex];
                if(depth<=900)
                {
                    piexls[colorIndex + BlueIndex] = 255;
                    piexls[colorIndex + GreenIndex] = 0;
                    piexls[colorIndex + RedIndex] = 0;
                }
                else if(depth>900&&depth<2000)
                {
                    piexls[colorIndex + BlueIndex] = 0;
                    piexls[colorIndex + GreenIndex] = 255;
                    piexls[colorIndex + RedIndex] = 0;
                }
                else if(depth>2000)
                {
                    piexls[colorIndex + BlueIndex] = 0;
                    piexls[colorIndex + GreenIndex] = 0;
                    piexls[colorIndex + RedIndex] = 255;
                }

                byte intensity = CalculateIntensityFromDepth(depth);
                piexls[colorIndex + BlueIndex] = intensity;
                piexls[colorIndex + GreenIndex] = intensity;
                piexls[colorIndex + RedIndex] = intensity;

                if(player>0)
                {
                    piexls[colorIndex + BlueIndex] = Colors.LightGreen.B;
                    piexls[colorIndex + GreenIndex] = Colors.LightGreen.G;
                    piexls[colorIndex + RedIndex] = Colors.LightGreen.R;
                }
            }
            return piexls;
        }

        void _kinect_AllFramesReady(object sender, AllFramesReadyEventArgs e)
        {
            //显示彩色摄像头
           using(ColorImageFrame colorFrame = e.OpenColorImageFrame())
           {
               if(colorFrame == null)
               {
                   return;
               }

               byte[] pixels = new byte[colorFrame.PixelDataLength];
               colorFrame.CopyPixelDataTo(pixels);

               //BGR32格式图片一个像素为4个字节
               int stride = colorFrame.Width * 4;
               ImageCamera.Source = BitmapSource.Create(colorFrame.Width, colorFrame.Height, 96, 96, PixelFormats.Bgr32, null, pixels, stride);

           }

            using(DepthImageFrame depthFrame = e.OpenDepthImageFrame())
            {
                if(depthFrame==null)
                {
                    return;
                }

                byte[] piexls = convertDepthFrameToColorFrame(depthFrame);

                int stride = depthFrame.Width * 4;
                imageDepth.Source = BitmapSource.Create(depthFrame.Width, depthFrame.Height, 96, 96, PixelFormats.Bgr32, null, piexls, stride);

            }

3、效果图

五、骨骼追踪

1、首先注释掉我们之前注册的时间，重新注册一个彩色数据流时间和一个骨骼事件，然后添加如下代码

private Skeleton[] skeletons;
        void _kinect_SkeletonFrameReady(object sender, SkeletonFrameReadyEventArgs e)
        {
            bool isSkeletonDataEeady = false;
            using (SkeletonFrame skeletonFrame = e.OpenSkeletonFrame())
            {
                if(skeletonFrame!=null)
                {
                    skeletons = new Skeleton[skeletonFrame.SkeletonArrayLength];
                    skeletonFrame.CopySkeletonDataTo(skeletons);
                    isSkeletonDataEeady = true;
                }

            }

            if(isSkeletonDataEeady==true)
            {
                Skeleton currentSkeleton = (from s in skeletons where s.TrackingState == SkeletonTrackingState.Tracked select s).FirstOrDefault();
                if(currentSkeleton !=null)
                {
                    lockHeadWithSpot(currentSkeleton);
                }
         
            }
        }

        void lockHeadWithSpot(Skeleton s)
        {
            Joint head = s.Joints[JointType.Head];
            ColorImagePoint colorPoint = _kinect.MapSkeletonPointToColor(head.Position, _kinect.ColorStream.Format);

            Point p = new Point((int)(ImageCamera.Width * colorPoint.X / _kinect.ColorStream.FrameWidth),
                                 (int)(ImageCamera.Height * colorPoint.Y / _kinect.ColorStream.FrameHeight));

            Canvas.SetLeft(ellipseHead, p.X);
            Canvas.SetRight(ellipseHead, p.Y);
        }

        void _kinect_ColorFrameReady(object sender, ColorImageFrameReadyEventArgs e)
        {
            using (ColorImageFrame colorFrame = e.OpenColorImageFrame())
            {
                if (colorFrame == null)
                {
                    return;
                }

                byte[] pixels = new byte[colorFrame.PixelDataLength];
                colorFrame.CopyPixelDataTo(pixels);

                //BGR32格式图片一个像素为4个字节
                int stride = colorFrame.Width * 4;
                ImageCamera.Source = BitmapSource.Create(colorFrame.Width, colorFrame.Height, 96, 96, PixelFormats.Bgr32, null, pixels, stride);

            }
           
        }

2、效果图

六关闭kinect设备

private void stopKinect()
        {
            if(_kinect != null)
            {
                if(_kinect.Status== KinectStatus.Connected)
                {
                    _kinect.Stop();
                }
            }
        }