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标题: 用于Kinect 的手势识别算法 [打印本页]

作者: 王者再临 时间: 2014-10-25 03:35
标题: 用于Kinect 的手势识别算法

* 本算法为DWT算法
* 输入: 两个时间序列矢量 A(a1,a2,a3,...an) B(b1,b2,b3,...bn)
* 输出: 一个关于两个序列矢量匹配度的数值
* 处理过程: 动态规划算法找最优解
* 原理:对于两个具有相同或相似特征的时间序列矢量元素其距离(欧几里得)之和最短

使用方法：（1）收集骨骼位置数据，如果用来手势识别则可以取 Hand,Wrist,elbow 等位置（格式如下所示）

                        @gesturename36.9032810/24/2014                   手势名
                           -0.0331086702644825                                     数据
                           -0.167759731411934
                           -0.206393882632256
                           -0.159131124615669
                           -0.856702625751495
                           -0.352049857378006
                           0.716807723045349
                        -0.580063939094543
                           1.17411589622498
                        -0.553598940372467
                        1.27646732330322
                        -0.494788020849228
                        ----

(2)使用 DynamicTimingWarping.Instance.LoadGesturesFromFile(file); 加载要识别的序列帧数据

Skeleton2DDataExtract.ProcessData(bodyData); 将每帧的数据加入

Skeleton2DDataExtract.Skeleton2DdataCoordReady += Skeleton2DdataCoordEventHandler; 获得一帧数据后的事件

DynamicTimingWarping.Instance.Recognize(arg.GetCoords()) 得到识别结果字符串

public class DynamicTimingWarping
{

      private static DynamicTimingWarping _instance;
      private readonly int _dimension;
      private readonly double _firstThreshold;
      private readonly double _minimumLength;
      private readonly double _globalThreshold;
      private readonly List<string> _labels;
      private readonly int _maxSlope;
      private List<List<double>> _sequences;
      public Dictionary<string, List<double>> sequencepairs = new Dictionary<string, List<double>>();

      public static DynamicTimingWarping Instance
{
      get
      {
         if (_instance != null)
         {
            return _instance;
         }
         else
         {
            _instance = new DynamicTimingWarping(12,0.6,2,2,10);
         }
         return _instance;
      }
}
      public void LoadGesturesFromFile(string fileLocation)
{
      int itemCount = 0;
      string line;
      string gestureName =  String.Empty;
      List<double> frames = new List<double>();
      System.IO.StreamReader file = new System.IO.StreamReader(fileLocation);
      while ((line = file.ReadLine()) != null)
      {
         if (line.StartsWith("@"))
         {
            gestureName = line;
            continue;
         }

         if (line.StartsWith("~"))
         {
            continue;
         }

         if (!line.StartsWith("----"))
         {
            frames.Add(Double.Parse(line));
         }

         itemCount++;
         if (line.StartsWith("----"))
         {
            AddOrUpdate(frames, gestureName);
            frames = new List<double>();
            gestureName = String.Empty;
         }
      }
      file.Close();
}

      public DynamicTimingWarping(int dim, double threshold, double firstThreshold, int ms, double minLen)
      {
         _dimension = dim;
         _sequences = new List<List<double>>();
         _labels = new List<string>();
         _globalThreshold = threshold;
         _firstThreshold = firstThreshold;
         _maxSlope = ms;
         _minimumLength = minLen;
      }

      public void AddOrUpdate(List<double> seq, string lab)
      {
         if (!sequencepairs.ContainsKey(lab))
         {
               _sequences.Add(seq);
               _labels.Add(lab);
               sequencepairs.Add(lab, seq);
               NGUIDebug.Log("手势数据添加成功 +1" + "名称 :" + lab);
         }

}

      public string Recognize(List<double> seq)
      {
         double minDist = double.PositiveInfinity;
         string classification = "未知手势";
         for (int i = 0; i < _sequences.Count; i++)
         {
            if (Dist2(seq,_sequences) < _firstThreshold)
            {
                  double d = Dtw(seq, _sequences) / _sequences.Count;
                  if (d < minDist)
                  {
                     minDist = d;
                     classification = (string)_labels;
                  }
            }
         }
         return (minDist < _globalThreshold ? classification : "未知手势");
      }

      public string RetrieveText()
      {
         string retStr = String.Empty;
         int count = 0;
         if (_sequences != null)
         {
            foreach (List<double> gusture in _sequences)
            {
                  retStr += _labels[count++] + "\r\n";
                  foreach (double db in gusture)
                  {
                     retStr += db + "\r\n";
                  }
                  retStr += "----";
                  if (count < _sequences.Count - 1)
                  {
                     retStr += "\r\n";
                  }
            }
         }
         return retStr;
      }

      public double Dtw(List<double> seq1R,List<double> seq2R)
      {
         var tab = new double[seq1R.Count + 1, seq2R.Count + 1];
         var slopeI = new int[seq1R.Count + 1, seq2R.Count + 1];
         var slopeJ = new int[seq1R.Count + 1, seq2R.Count + 1];

         for (int i = 0; i < seq1R.Count + 1; i++)
         {
            for (int j = 0; j < seq2R.Count + 1; j++)
            {
                  tab[i, j] = double.PositiveInfinity;
                  slopeI[i, j] = 0;
                  slopeJ[i, j] = 0;
            }
         }

         tab[0, 0] = 0;
         for (int i = 1; i < seq1R.Count + 1; i++)
         {
            for (int j = 1; j < seq2R.Count + 1; j++)
            {
                  if (tab[i, j - 1] < tab[i - 1, j - 1] && tab[i, j - 1] < tab[i - 1, j] &&
                     slopeI[i, j - 1] < _maxSlope)
                  {
                     tab[i, j] = Dist21(seq1R[i - 1], seq2R[j - 1]) + tab[i, j - 1];
                     slopeI[i, j] = slopeJ[i, j - 1] + 1;
                     slopeJ[i, j] = 0;
                  }
                  else if (tab[i - 1, j] < tab[i - 1, j - 1] && tab[i - 1, j] < tab[i, j - 1] &&
                           slopeJ[i - 1, j] < _maxSlope)
                  {
                     tab[i, j] = Dist21(seq1R[i - 1],seq2R[j - 1]) + tab[i - 1, j];
                     slopeI[i, j] = 0;
                     slopeJ[i, j] = slopeJ[i - 1, j] + 1;
                  }
                  else
                  {
                     tab[i, j] = Dist21(seq1R[i - 1], seq2R[j - 1]) + tab[i - 1, j - 1];
                     slopeI[i, j] = 0;
                     slopeJ[i, j] = 0;
                  }
            }
         }
         double bestMatch = double.PositiveInfinity;
         for (int i = 1; i < (seq1R.Count + 1) - _minimumLength; i++)
         {
            if (tab[i, seq2R.Count] < bestMatch)
            {
                  bestMatch = tab[i, seq2R.Count];
            }
         }

         return bestMatch;
      }
      private double Dist2(List<double> a, List<double> b)
      {
         double d = 0;
         for (int i = 0; i < _dimension; i++)
         {
            d += Math.Pow(a - b, 2);
         }

return Math.Sqrt(d);
}

      private double Dist21(double a,double b)
      {
         return  Mathf.Sqrt((float)Math.Pow(a-b,2));
      }
}

class Skeleton2DDataExtract
{

public delegate void Skeleton2DdataCoordEventHandler(object sender,BodydataCoordEventArgs a);

      public static event Skeleton2DdataCoordEventHandler Skeleton2DdataCoordReady;

      public static void ProcessData(KinectInterop.BodyData data)
      {
         Vector2 [] p = new Vector2[6];
         Vector2 shoulderRight = new Vector2(), shoulderLeft = new Vector2();
         for (int i = 0; i < data.joint.Length;i++)
         {
            JointType j =  data.joint.jointType;
            switch (j)
            {
                  case JointType.HandLeft:
                     p[0] = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.WristLeft:
                     p[1] = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.ElbowLeft:
                     p[2] = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.ElbowRight:
                     p[3] = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.WristRight:
                     p[4] = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.HandRight:
                     p[5] = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.ShoulderLeft:
                     shoulderLeft = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
                  case JointType.ShoulderRight:
                     shoulderRight = new Vector2(data.joint.kinectPos.x, data.joint.kinectPos.y);
                     break;
            }
         }

         var center = new Vector2((shoulderLeft.x + shoulderRight.x) / 2, (shoulderLeft.y + shoulderRight.y) / 2);
         for (int i = 0; i < 6; i++)
         {
            p.x -= center.x;
            p.y -= center.y;
         }

         double shoulderDist =
                        Mathf.Sqrt(Mathf.Pow((shoulderLeft.x - shoulderRight.x), 2) +
                        Mathf.Pow((shoulderLeft.y - shoulderRight.y), 2));
         for (int i = 0; i < 6; i++)
         {
            p.x /= (float)shoulderDist;
            p.y /= (float)shoulderDist;
         }
         if (Skeleton2DdataCoordReady !=null)
         Skeleton2DdataCoordReady(null, new BodydataCoordEventArgs(p));
      }
}

public class BodydataCoordEventArgs
{
      private readonly Vector2[] _points;
      public BodydataCoordEventArgs(Vector2[] points)
      {
         _points = (Vector2[])points.Clone();
      }

      public Vector2 GetPoint(int index)
      {
         return _points[index];
      }

      internal  List<double> GetCoords()
      {
         List<double> temp = new List<double>();
         for (int i = 0; i < _points.Length; i++)
         {
            temp.Add(_points.x);
            temp.Add(_points.y);
         }
         return temp;
   }
}

作者: hyui 时间: 2014-10-25 03:55
Good to learn !

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