/// <summary>
/// Function of initialisation : launch every functions to have all needed data for emotionRecognition
/// </summary>
public static void init()
{
StreamReader sr = new StreamReader(nameForDb, Encoding.Default);
//Count the exact number of lines the database
int i = 0;
string buff = "a";
while (buff != null)
{
buff = sr.ReadLine();
if (buff == null)
{
break;
}
else
{
i++;
}
}
//Try to load files with data (path, numberOfLines)
dataParsed = new Parsing(nameForDb, i);
//Catch results of eigenFace
if (dimension == 2)
{
eigen = new EigenFace(dataParsed.data);
}
else if (dimension == 3)
{
eigen = new EigenFace3D(dataParsed.data);
}
else
{
throw new System.InvalidOperationException("Problem of dimension in FaceRecognizer");
}
}
/// <summary>
/// Provide the emotion of the nearest face of the current face get with the kinect
/// </summary>
///
/// <param name="skeletonFaceTracker">SkeletonFaceTracker</param>
public static void recognizer(SkeletonFaceTracker skeletonFaceTracker)
{
EigenMethod eigenToRec = null;
if (dimension == 3)
{
//Get all needed date from the 3D set of points : eigenValues and distances between each faces
eigenToRec = new EigenFace3D(skeletonFaceTracker.facePoints3D);
}
else if (dimension == 2)
{
//Get all needed date from the 2D set of points : eigenValues and distances between each faces
eigenToRec = new EigenFace(skeletonFaceTracker.facePoints);
}
//For each variable whose name contains "espilon" we work on [i,j] with 0 <= i,j <= 3 corresponding to the coordinates of the 3 eigenVectors we chose to keep
//Calculate the nearest face
double minI = -1;
int indice = -1;
for (int i = 0; i < eigen.epsilon.GetLength(1); i++)
{
if (minI == -1)
{
minI = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilon[0, 0] - eigen.epsilon[0, 0], 2) + Math.Pow(eigenToRec.vEpsilon[1, 0] - eigen.epsilon[1, 0], 2) + Math.Pow(eigenToRec.vEpsilon[2, 0] - eigen.epsilon[2, 0], 2)));
indice = i;
}
else
{
if (minI > (Math.Sqrt(Math.Pow(eigenToRec.vEpsilon[0, 0] - eigen.epsilon[0, i], 2) + Math.Pow(eigenToRec.vEpsilon[1, 0] - eigen.epsilon[1, i], 2) + Math.Pow(eigenToRec.vEpsilon[2, 0] - eigen.epsilon[2, i], 2))))
{
minI = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilon[0, 0] - eigen.epsilon[0, i], 2) + Math.Pow(eigenToRec.vEpsilon[1, 0] - eigen.epsilon[1, i], 2) + Math.Pow(eigenToRec.vEpsilon[2, 0] - eigen.epsilon[2, i], 2)));
indice = i;
}
}
}
//calculate the nearest face according only to the mouth
double min = -1;
int indiceM = -1;
for (int i = 1; i < eigen.epsilonM.GetLength(1); i++)
{
if (min == -1)
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonM[0, 0] - eigen.epsilonM[0, 0], 2) + Math.Pow(eigenToRec.vEpsilonM[1, 0] - eigen.epsilonM[1, 0], 2) + Math.Pow(eigenToRec.vEpsilonM[2, 0] - eigen.epsilonM[2, 0], 2)));
indiceM = i;
}
else
{
if (min > (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonM[0, 0] - eigen.epsilonM[0, i], 2) + Math.Pow(eigenToRec.vEpsilonM[1, 0] - eigen.epsilonM[1, i], 2) + Math.Pow(eigenToRec.vEpsilonM[2, 0] - eigen.epsilonM[2, i], 2))))
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonM[0, 0] - eigen.epsilonM[0, i], 2) + Math.Pow(eigenToRec.vEpsilonM[1, 0] - eigen.epsilonM[1, i], 2) + Math.Pow(eigenToRec.vEpsilonM[2, 0] - eigen.epsilonM[2, i], 2)));
indiceM = i;
}
}
}
//calculate the nearest face according only to the left eye
min = -1;
int indiceEyeL = -1;
for (int i = 1; i < eigen.epsilonEyeL.GetLength(1); i++)
{
if (min == -1)
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeL[0, 0] - eigen.epsilonEyeL[0, 0], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[1, 0] - eigen.epsilonEyeL[1, 0], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[2, 0] - eigen.epsilonEyeL[2, 0], 2)));
indiceEyeL = i;
}
else
{
if (min > (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeL[0, 0] - eigen.epsilonEyeL[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[1, 0] - eigen.epsilonEyeL[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[2, 0] - eigen.epsilonEyeL[2, i], 2))))
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeL[0, 0] - eigen.epsilonEyeL[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[1, 0] - eigen.epsilonEyeL[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[2, 0] - eigen.epsilonEyeL[2, i], 2)));
indiceEyeL = i;
}
}
}
//calculate the nearest face according only to the right eye
min = -1;
int indiceEyeR = -1;
for (int i = 1; i < eigen.epsilonEyeR.GetLength(1); i++)
{
if (min == -1)
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeR[0, 0] - eigen.epsilonEyeR[0, 0], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[1, 0] - eigen.epsilonEyeR[1, 0], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[2, 0] - eigen.epsilonEyeR[2, 0], 2)));
indiceEyeR = i;
}
else
{
if (min > (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeR[0, 0] - eigen.epsilonEyeR[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[1, 0] - eigen.epsilonEyeR[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[2, 0] - eigen.epsilonEyeR[2, i], 2))))
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeR[0, 0] - eigen.epsilonEyeR[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[1, 0] - eigen.epsilonEyeR[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[2, 0] - eigen.epsilonEyeR[2, i], 2)));
indiceEyeR = i;
}
}
}
//calculate the nearest face according to all calculations above
min = -1;
int indiceAll = -1;
for (int i = 1; i < eigen.epsilon.GetLength(1); i++)
{
if (min == -1)
{
min = (Math.Sqrt(Math.Pow(eigenToRec.vEpsilonM[0, 0] - eigen.epsilonM[0, 0], 2) + Math.Pow(eigenToRec.vEpsilonM[1, 0] - eigen.epsilonM[1, 0], 2) + Math.Pow(eigenToRec.vEpsilonM[2, 0] - eigen.epsilonM[2, 0], 2)));
indiceAll = i;
}
else
{
if (min > (Math.Sqrt(Math.Pow(eigenToRec.vEpsilon[0, 0] - eigen.epsilonM[0, i], 2) + Math.Pow(eigenToRec.vEpsilon[1, 0] - eigen.epsilonM[1, i], 2) + Math.Pow(eigenToRec.vEpsilon[2, 0] - eigen.epsilonM[2, i], 2))) + Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeL[0, 0] - eigen.epsilonEyeL[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[1, 0] - eigen.epsilonEyeL[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[2, 0] - eigen.epsilonEyeL[2, i], 2)) + Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeR[0, 0] - eigen.epsilonEyeR[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[1, 0] - eigen.epsilonEyeR[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[2, 0] - eigen.epsilonEyeR[2, i], 2)))
{
min = Math.Sqrt(Math.Pow(eigenToRec.vEpsilon[0, 0] - eigen.epsilonM[0, i], 2) + Math.Pow(eigenToRec.vEpsilon[1, 0] - eigen.epsilonM[1, i], 2) + Math.Pow(eigenToRec.vEpsilon[2, 0] - eigen.epsilonM[2, i], 2)) + Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeL[0, 0] - eigen.epsilonEyeL[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[1, 0] - eigen.epsilonEyeL[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeL[2, 0] - eigen.epsilonEyeL[2, i], 2)) + Math.Sqrt(Math.Pow(eigenToRec.vEpsilonEyeR[0, 0] - eigen.epsilonEyeR[0, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[1, 0] - eigen.epsilonEyeR[1, i], 2) + Math.Pow(eigenToRec.vEpsilonEyeR[2, 0] - eigen.epsilonEyeR[2, i], 2));
indiceAll = i;
}
}
}
int bestIndice = indice;
if (min < minI)
{
bestIndice = indiceAll;
}
//the nearest emotion is updated
nearest = dataParsed.emotions[bestIndice];
emotionEvent(null, new EmotionEventArgs(nearest));
}
