std::vector<cv::Mat> SiftMatcher::compute(Keypoints& keypoints)
{
std::vector<cv::Mat> descriptors(keypoints.size());
cv::SiftDescriptorExtractor extractor;
for (size_t i = 0; i < keypoints.size(); ++i)
{
extractor.compute(m_images[i], keypoints[i], descriptors[i]);
}
return descriptors;
}
bool FeatureAlgorithm::extractFeatures(const cv::Mat& image, Keypoints& kp, Descriptors& desc) const
{
assert(!image.empty());
if (featureEngine)
{
(*featureEngine)(image, cv::noArray(), kp, desc);
}
else
{
detector->detect(image, kp);
if (kp.empty())
return false;
extractor->compute(image, kp, desc);
}
return kp.size() > 0;
}
bool performEstimation
(
const FeatureAlgorithm& alg,
const ImageTransformation& transformation,
const cv::Mat& sourceImage,
std::vector<FrameMatchingStatistics>& stat
)
{
Keypoints sourceKp;
Descriptors sourceDesc;
cv::Mat gray;
if (sourceImage.channels() == 3)
cv::cvtColor(sourceImage, gray, CV_BGR2GRAY);
else if (sourceImage.channels() == 4)
cv::cvtColor(sourceImage, gray, CV_BGRA2GRAY);
else if(sourceImage.channels() == 1)
gray = sourceImage;
if (!alg.extractFeatures(gray, sourceKp, sourceDesc))
return false;
std::vector<float> x = transformation.getX();
stat.resize(x.size());
const int count = x.size();
cv::Mat transformedImage;
Keypoints resKpReal;
Descriptors resDesc;
Matches matches;
// To convert ticks to milliseconds
const double toMsMul = 1000. / cv::getTickFrequency();
#pragma omp parallel for private(transformedImage, resKpReal, resDesc, matches)
for (int i = 0; i < count; i++)
{
float arg = x[i];
FrameMatchingStatistics& s = stat[i];
transformation.transform(arg, gray, transformedImage);
int64 start = cv::getTickCount();
alg.extractFeatures(transformedImage, resKpReal, resDesc);
// Initialize required fields
s.isValid = resKpReal.size() > 0;
s.argumentValue = arg;
if (!s.isValid)
continue;
if (alg.knMatchSupported)
{
std::vector<Matches> knMatches;
alg.matchFeatures(sourceDesc, resDesc, 2, knMatches);
ratioTest(knMatches, 0.75, matches);
// Compute percent of false matches that were rejected by ratio test
s.ratioTestFalseLevel = (float)(knMatches.size() - matches.size()) / (float) knMatches.size();
}
else
{
alg.matchFeatures(sourceDesc, resDesc, matches);
}
int64 end = cv::getTickCount();
Matches correctMatches;
cv::Mat homography;
bool homographyFound = ImageTransformation::findHomography(sourceKp, resKpReal, matches, correctMatches, homography);
// Some simple stat:
s.isValid = homographyFound;
s.totalKeypoints = resKpReal.size();
s.consumedTimeMs = (end - start) * toMsMul;
// Compute overall percent of matched keypoints
s.percentOfMatches = (float) matches.size() / (float)(std::min(sourceKp.size(), resKpReal.size()));
s.correctMatchesPercent = (float) correctMatches.size() / (float)matches.size();
// Compute matching statistics
computeMatchesDistanceStatistics(correctMatches, s.meanDistance, s.stdDevDistance);
}
return true;
}