void FeatureMatchThread::run()
{
Mat resultImg;
Mat grayImg;
cvtColor(cropImg,grayImg,CV_BGR2GRAY);
featureDetector.detect(grayImg,keyPoints);
featureExtractor.compute(grayImg,keyPoints,descriptors);
flannIndex.build(descriptors,flann::LshIndexParams(12,20,2),cvflann::FLANN_DIST_HAMMING);
while(true)
{
Mat captureImage_gray;
vector<KeyPoint> captureKeyPoints;
Mat captureDescription;
vector<DMatch> goodMatches;
cap >> captureImage;
if(captureImage.empty())
continue;
cvtColor(captureImage,captureImage_gray,CV_BGR2GRAY);
featureDetector.detect(captureImage_gray,captureKeyPoints);
featureExtractor.compute(captureImage_gray,captureKeyPoints,captureDescription);
Mat matchIndex(captureDescription.rows,2,CV_32SC1);
Mat matchDistance(captureDescription.rows,2,CV_32FC1);
flannIndex.knnSearch(captureDescription,matchIndex,matchDistance,2,flann::SearchParams());
for(int i=0;i<matchDistance.rows;i++)
{
if(matchDistance.at<float>(i,0) < 0.6 * matchDistance.at<float>(i,1))
{
DMatch dmatches(i,matchIndex.at<int>(i,0),matchDistance.at<float>(i,0));
goodMatches.push_back(dmatches);
}
}
drawMatches(captureImage,captureKeyPoints,cropImg,keyPoints,goodMatches,resultImg);
emit NewFeatureMatch(&resultImg);
imshow(WindowName,captureImage);
cv::setMouseCallback(WindowName,mouse_callback);
captureKeyPoints.clear();
goodMatches.clear();
waitKey(30);
}
return;
}
void YawAngleEstimator::Indexmatch(Mat& CurrentDescriptors, float* CurrentVote)
{
//Lowe's Algorithm to caculate vote for each angletemplate
for (int i = 4; i < AngleNum; i++)
{
//rows:numbers of keypoints
Mat matchIndex(CurrentDescriptors.rows, 2, CV_32SC1), matchDistance(CurrentDescriptors.rows, 2, CV_32FC1);
CurrentVote[i] = 0;
//cout << CurrentDescriptors[0] << endl;
YawIndex[i].knnSearch(CurrentDescriptors, matchIndex, matchDistance, 2, flann::SearchParams());
for (int j = 0; j < matchDistance.rows; j++)
{
if (matchDistance.at<float>(j, 0) < 0.6*matchDistance.at<float>(j, 1))
++CurrentVote[i];
}
}
}
