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Added plot data generation for visual descriptors comparison in the evaluation framework

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This commit is contained in:
Ilya Lysenkov
2010-06-11 09:38:39 +00:00
parent f6f634bace
commit 88bd1f1d1a
3 changed files with 241 additions and 19 deletions
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37
modules/features2d/src/descriptors.cpp
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@@ -44,6 +44,8 @@
using namespace std;
using namespace cv;
//#define _KDTREE
/****************************************************************************************\
* DescriptorExtractor *
\****************************************************************************************/
@@ -332,15 +334,27 @@ void OneWayDescriptorMatch::add( KeyPointCollection& keypoints )
void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, vector<int>& indices)
{
vector<DescriptorMatching> matchings( points.size() );
indices.resize(points.size());
match( image, points, matchings );
for( size_t i = 0; i < points.size(); i++ )
indices[i] = matchings[i].index;
}
void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, vector<DescriptorMatching>& matchings )
{
matchings.resize( points.size() );
IplImage _image = image;
for( size_t i = 0; i < points.size(); i++ )
{
int descIdx = -1;
int poseIdx = -1;
float distance;
base->FindDescriptor( &_image, points[i].pt, descIdx, poseIdx, distance );
indices[i] = descIdx;
DescriptorMatching matching;
matching.index = -1;
base->FindDescriptor( &_image, points[i].pt, matching.index, poseIdx, matching.distance );
matchings[i] = matching;
}
}
@@ -631,6 +645,21 @@ void FernDescriptorMatch::match( const Mat& image, vector<KeyPoint>& keypoints,
}
}
void FernDescriptorMatch::match( const Mat& image, vector<KeyPoint>& keypoints, vector<DescriptorMatching>& matchings )
{
trainFernClassifier();
matchings.resize( keypoints.size() );
vector<float> signature( (size_t)classifier->getClassCount() );
for( size_t pi = 0; pi < keypoints.size(); pi++ )
{
calcBestProbAndMatchIdx( image, keypoints[pi].pt, matchings[pi].distance, matchings[pi].index, signature );
//matching[pi].distance is log of probability so we need to transform it
matchings[pi].distance = -matchings[pi].distance;
}
}
void FernDescriptorMatch::classify( const Mat& image, vector<KeyPoint>& keypoints )
{
trainFernClassifier();