void Learn(short[,] imageData)
{
currentSampleCount++;
double[] feature = imgFeature.GenerateFeature(imageData);
featureVector.Add(feature);
if (this.GestureDataReady)
{
this.ImageCollectionFinished(this, null);
}
this.learning = false;
}
void Classify(object state)
{
short[,] imageData = (short[, ])state;
double[] feature = imgFeature.GenerateFeature(imageData);
int label = (int)svm.svm_predict(modelBuilder.GetModel(), MatrixUtil.DoubleToSvmNode(feature));
this.category = label;
if (this.CategoryDetected != null)
{
this.CategoryDetected(this, new CategoryEventArgs()
{
CategoryLabel = this.category
});
}
this.classifying = false;
}
