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Homography error computation added
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@BloodAxe
BloodAxe committed Aug 27, 2012
1 parent 8fd9fa1 commit 01481ad
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Showing 6 changed files with 251 additions and 189 deletions.
223 changes: 115 additions & 108 deletions AlgorithmEstimation.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2,128 +2,135 @@

bool computeMatchesDistanceStatistics(const Matches& matches, float& meanDistance, float& stdDev)
{
if (matches.empty())
if (matches.empty())
return false;

std::vector<float> distances(matches.size());
for (size_t i=0; i<matches.size(); i++)
distances[i] = matches[i].distance;

cv::Scalar mean, dev;
cv::meanStdDev(distances, mean, dev);

meanDistance = static_cast<float>(mean.val[0]);
stdDev = static_cast<float>(dev.val[0]);

return false;

std::vector<float> distances(matches.size());
for (size_t i=0; i<matches.size(); i++)
distances[i] = matches[i].distance;

cv::Scalar mean, dev;
cv::meanStdDev(distances, mean, dev);

meanDistance = static_cast<float>(mean.val[0]);
stdDev = static_cast<float>(dev.val[0]);

return false;
}

void ratioTest(const std::vector<Matches>& knMatches, float maxRatio, Matches& goodMatches)
{
goodMatches.clear();

for (size_t i=0; i< knMatches.size(); i++)
{
const cv::DMatch& best = knMatches[i][0];
const cv::DMatch& good = knMatches[i][1];

assert(best.distance <= good.distance);
float ratio = (best.distance / good.distance);

if (ratio <= maxRatio)
goodMatches.clear();

for (size_t i=0; i< knMatches.size(); i++)
{
goodMatches.push_back(best);
const cv::DMatch& best = knMatches[i][0];
const cv::DMatch& good = knMatches[i][1];

assert(best.distance <= good.distance);
float ratio = (best.distance / good.distance);

if (ratio <= maxRatio)
{
goodMatches.push_back(best);
}
}
}
}

bool performEstimation
(
const FeatureAlgorithm& alg,
const ImageTransformation& transformation,
const cv::Mat& sourceImage,
std::vector<FrameMatchingStatistics>& stat
)
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();

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)
for (int i = 0; i < count; i++)
{
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();
float arg = x[i];
FrameMatchingStatistics& s = stat[i];

transformation.transform(arg, gray, transformedImage);
cv::Mat expectedHomography = transformation.getHomography(arg, gray);


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);

if (homographyFound)
{
s.homographyError = cv::norm(expectedHomography * homography.inv(), cv::NORM_INF);
}
}
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;

return true;
}

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