private void btnApplyTransformation_Click(object sender, EventArgs e)
{
Transformation align = LLSOTransform.ComputeTransformation(Shape1, Shape2);
MessageBox.Show("Cost = " + LLSOTransform.ComputeCost(Shape1, Shape2, align).ToString());
List <Point> Shape2Transformed = ApplyTransformation(align, Shape2);
Pen pRed = new Pen(Brushes.Red, 1);
Pen pBlue = new Pen(Brushes.Blue, 1);
Graphics g = panTransformed.CreateGraphics();
DisplayShape(Shape1, pBlue, g);
DisplayShape(Shape2Transformed, pRed, g);
}
List <Point>[] ExhaustiveEvaluation()
{
List <Point> Shape1Temp;
List <Point> Shape2Temp;
List <Point> Shape1NoOutliers = new List <Point>(Shape1);
List <Point> Shape2NoOutliers = new List <Point>(Shape2);
Transformation transform = LLSOTransform.ComputeTransformation(Shape1, Shape2);
double prevcost = LLSOTransform.ComputeCost(Shape1, Shape2, transform);
double costwithoutI = 0;
int count = Shape1NoOutliers.Count;
int i = 0;
while (i < count)
{
Shape1Temp = new List <Point>(Shape1NoOutliers);
Shape2Temp = new List <Point>(Shape2NoOutliers);
Shape1Temp.RemoveAt(i);
Shape2Temp.RemoveAt(i);
transform = LLSOTransform.ComputeTransformation(Shape1Temp, Shape2Temp);
costwithoutI = LLSOTransform.ComputeCost(Shape1Temp, Shape2Temp, transform);
//MessageBox.Show("New Cost = " + costwithoutI.ToString());
if (costwithoutI < (prevcost * 0.8))
{
Shape1NoOutliers.RemoveAt(i);
Shape2NoOutliers.RemoveAt(i);
Shape2NoOutliers = ApplyTransformation(transform, Shape2NoOutliers);
i--;//since every element with greater index is moved to the rigth
count--;
prevcost = costwithoutI;
MessageBox.Show("New Cost = " + costwithoutI.ToString());
}
i++;
}
List <Point>[] shapesNoOutliers = { Shape1NoOutliers, Shape2NoOutliers };
return(shapesNoOutliers);
}
List <Point>[] Ransac(int minPointsNum, int iterNum, double threshold, int requiredPointsNum, out Transformation bestModel)
{
//data is Shape1, Shape2 globally accessible
bestModel = new Transformation();
List <Point>[] bestConsensusSet = new List <Point> [2];
double bestError = 10000;
int iteration = 0;
List <Point>[] maybeInliers = new List <Point> [2];
List <Point>[] maybeOutliers = new List <Point> [2];
Transformation maybeModel = new Transformation();
List <Point>[] consensusSet = new List <Point> [2];
Random random = new Random();
while (iteration < iterNum)
{
maybeOutliers[0] = new List <Point>(Shape1);
maybeOutliers[1] = new List <Point>(Shape2);
maybeInliers[0] = new List <Point>();
maybeInliers[1] = new List <Point>();
int[] intArray = Enumerable.Range(0, Shape1.Count).OrderBy(t => random.Next()).Take(minPointsNum).ToArray();//Range(start,countOfElem)
foreach (int x in intArray)
{
maybeInliers[0].Add(Shape1[x]);
maybeInliers[1].Add(Shape2[x]);
maybeOutliers[0].Remove(Shape1[x]);
maybeOutliers[1].Remove(Shape2[x]);
}
maybeModel = LLSOTransform.ComputeTransformation(maybeInliers[0], maybeInliers[1]);
consensusSet[0] = new List <Point>(maybeInliers[0]);
consensusSet[1] = new List <Point>(maybeInliers[1]);
//for every point in data not in maybe_inliers, meaning is in maybe_outliers
for (int i = 0; i < maybeOutliers[0].Count; i++)
{
if (LLSOTransform.ComputeCost(maybeOutliers[0][i], maybeOutliers[1][i], maybeModel) < threshold)
{
consensusSet[0].Add(maybeOutliers[0][i]);
consensusSet[1].Add(maybeOutliers[1][i]);
}
}
if (consensusSet[0].Count > requiredPointsNum)
{
//implies that we may have found a good model, now test how good it is
Transformation better_model = LLSOTransform.ComputeTransformation(consensusSet[0], consensusSet[1]);
double thisError = LLSOTransform.ComputeCost(consensusSet[0], consensusSet[1], better_model);
if (thisError < bestError)
{
//we have found a model which is better than any of the previous ones
bestModel.A = better_model.A;
bestModel.B = better_model.B;
bestModel.T1 = better_model.T1;
bestModel.T2 = better_model.T2;
//sort consensus set accoring to inital shape order of connections
bestConsensusSet[0] = consensusSet[0].OrderBy(item => Shape1.IndexOf(item)).ToList();
bestConsensusSet[1] = consensusSet[1].OrderBy(item => Shape2.IndexOf(item)).ToList();
bestError = thisError;
}
}
iteration++;
}
MessageBox.Show("New Cost = " + bestError.ToString());
return(bestConsensusSet);
}
