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Updated the support for color-names features and fixing some typos

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This commit is contained in:
Kurnianggoro
2015-06-08 00:45:03 +09:00
parent df9adff577
commit f77a46167f
2 changed files with 78 additions and 35 deletions
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4
modules/tracking/include/opencv2/tracking/tracker.hpp
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@@ -1189,8 +1189,8 @@ class CV_EXPORTS_W TrackerTLD : public Tracker
BOILERPLATE_CODE("TLD",TrackerTLD);
};
/** @brief KCF is a novel tracking framework that utilize properties of circulant matrix to enhance the processing speed.
* This tracking method is implementation of @cite KCF_ECCV which is extended to KFC with color-names features (@cite KCF_CN).
/** @brief KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed.
* This tracking method is an implementation of @cite KCF_ECCV which is extended to KFC with color-names features (@cite KCF_CN).
* The original paper of KCF is available at <http://home.isr.uc.pt/~henriques/circulant/index.html>
* as well as the matlab implementation. For more information about KCF with color-names features, please refer to
* <http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/index.html>.

109
modules/tracking/src/trackerKCF.cpp
View File

@@ -88,8 +88,11 @@ namespace cv{
* KCF functions and vars
*/
void createHanningWindow(OutputArray _dst, const cv::Size winSize, const int type) const;
void inline fft2(const Mat src, std::vector<Mat> & dest) const;
void inline fft2(const Mat src, Mat & dest) const;
void inline ifft2(const Mat src, Mat & dest) const ;
void inline ifft2(const Mat src, Mat & dest) const ;
void inline pixelWiseMult(const std::vector<Mat> src1, const std::vector<Mat> src2, std::vector<Mat> & dest, const int flags, const bool conjB=false) const;
void inline sumChannels(std::vector<Mat> src, Mat & dest) const;
bool getSubWindow(const Mat img, const Rect roi, Mat& patch) const;
void extractCN(Mat _patch, Mat & cnFeatures) const;
void denseGaussKernel(const double sigma, const Mat _x, const Mat _y, Mat & _k) const;
@@ -127,6 +130,8 @@ namespace cv{
{
isInit = false;
resizeImage = false;
CV_Assert(params.descriptor == GRAY || params.descriptor == CN /*|| params.descriptor == CN2*/);
}
void TrackerKCFImpl::read( const cv::FileNode& fn ){
@@ -163,7 +168,7 @@ namespace cv{
// add padding to the roi
roi.x-=roi.width/2;
roi.y-=roi.height/2+1;
roi.y-=roi.height/2;
roi.width*=2;
roi.height*=2;
@@ -173,7 +178,6 @@ namespace cv{
Mat layers[] = {hann, hann, hann, hann, hann, hann, hann, hann, hann, hann};
merge(layers, 10, hann);
}
if(params.descriptor != GRAY){printf("The choosen descriptor mode is not available! Please use GRAY descriptor, other descriptors will be avaiable soon.\n");return false;}//temporary, will be updated soon
// create gaussian response
y=Mat::zeros((int)roi.height,(int)roi.width,CV_64F);
@@ -229,18 +233,19 @@ namespace cv{
// Kernel Regularized Least-Squares, calculate alphas
denseGaussKernel(params.sigma,x,x,k);
fft2(k,kf);
kf=kf+params.lambda;
/* TODO: optimize this element-wise division
* new_alphaf=yf./kf
* z=[(ax+bd)+i(bc-ad)]/(c^2+d^2)
* z=(a+bi)/(c+di)[(ac+bd)+i(bc-ad)]/(c^2+d^2)
*/
new_alphaf=Mat_<Vec2d >(yf.rows, yf.cols);
std::complex<double> temp;
for(int i=0;i<yf.rows;i++){
for(int j=0;j<yf.cols;j++){
temp=std::complex<double>(yf.at<Vec2d>(i,j)[0],yf.at<Vec2d>(i,j)[1])/(std::complex<double>(kf.at<Vec2d>(i,j)[0],kf.at<Vec2d>(i,j)[1])/*+complex<float>(0.0000000001,0.0000000001)*/);
temp=std::complex<double>(yf.at<Vec2d>(i,j)[0],yf.at<Vec2d>(i,j)[1])/(std::complex<double>(kf.at<Vec2d>(i,j)[0],kf.at<Vec2d>(i,j)[1])/*+std::complex<double>(0.0000000001,0.0000000001)*/);
new_alphaf.at<Vec2d >(i,j)[0]=temp.real();
new_alphaf.at<Vec2d >(i,j)[1]=temp.imag();
}
@@ -250,7 +255,7 @@ namespace cv{
new_z=x.clone();
if(frame==0){
alphaf=new_alphaf.clone();
z=x;
z=x.clone();
}else{
alphaf=(1.0-params.interp_factor)*alphaf+params.interp_factor*new_alphaf;
z=(1.0-params.interp_factor)*z+params.interp_factor*new_z;
@@ -309,21 +314,62 @@ namespace cv{
}
/*
* simplification of fourier transoform function in opencv
* simplification of fourier transform function in opencv
*/
void inline TrackerKCFImpl::fft2(const Mat src, Mat & dest)const {
Mat planes[] = {Mat_<double>(src), Mat::zeros(src.size(), CV_64F)};
merge(planes, 2, dest);
dft(dest,dest,DFT_COMPLEX_OUTPUT);
std::vector<Mat> layers(src.channels());
std::vector<Mat> outputs(src.channels());
split(src, layers);
for(int i=0;i<src.channels();i++){
dft(layers[i],outputs[i],DFT_COMPLEX_OUTPUT);
}
merge(outputs,dest);
}
void inline TrackerKCFImpl::fft2(const Mat src, std::vector<Mat> & dest) const{
std::vector<Mat> layers(src.channels());
dest.clear();
dest.resize(src.channels());
split(src, layers);
for(int i=0;i<src.channels();i++){
dft(layers[i],dest[i],DFT_COMPLEX_OUTPUT);
}
}
/*
* simplification of inverse fourier transoform function in opencv
* simplification of inverse fourier transform function in opencv
*/
void inline TrackerKCFImpl::ifft2(const Mat src, Mat & dest)const {
idft(src,dest,DFT_SCALE+DFT_REAL_OUTPUT);
}
/*
* Point-wise multiplication of two Multichannel Mat data
*/
void inline TrackerKCFImpl::pixelWiseMult(const std::vector<Mat> src1, const std::vector<Mat> src2, std::vector<Mat> & dest, const int flags, const bool conjB) const{
dest.clear();
dest.resize(src1.size());
for(unsigned i=0;i<src1.size();i++){
mulSpectrums(src1[i], src2[i], dest[i],flags,conjB);
}
}
/*
* Combines all channels in a multi-channels Mat data into a single channel
*/
void inline TrackerKCFImpl::sumChannels(std::vector<Mat> src, Mat & dest) const{
dest=src[0].clone();
for(unsigned i=1;i<src.size();i++){
dest+=src[i];
}
}
/*
* obtain the patch and apply hann window filter to it
*/
@@ -356,24 +402,24 @@ namespace cv{
addRight=(_roi.width+_roi.x>img.cols?_roi.width+_roi.x-img.cols:0);
copyMakeBorder(patch,patch,addTop,addBottom,addLeft,addRight,BORDER_REPLICATE);
if(patch.rows==0 || patch.cols==0)return false;
// extract the desired descriptors
switch(params.descriptor){
case GRAY:
if(img.channels()>1)cvtColor(patch,patch, CV_BGR2GRAY);
patch.convertTo(patch,CV_64F);
patch=patch/255.0-0.5; // normalize to range -0.5 .. 0.5
break;
case CN:
CV_Assert(img.channels() == 3);
extractCN(patch,patch);
break;
default:
case CN2:
if(patch.channels()>1)cvtColor(patch,patch, CV_BGR2GRAY);
break;
}
patch.convertTo(patch,CV_64F);
patch=patch/255.0-0.5; // normalize to range -0.5 .. 0.5
patch=patch.mul(hann); // hann window filter
return true;
@@ -407,25 +453,26 @@ namespace cv{
* dense gauss kernel function
*/
void TrackerKCFImpl::denseGaussKernel(const double sigma, const Mat _x, const Mat _y, Mat & _k)const{
Mat _xf, _yf, xyf,xy;
std::vector<Mat> _xf,_yf,xyf_v;
Mat xy,xyf;
double normX, normY;
fft2(_x,_xf);
fft2(_y,_yf);
normX=norm(_x);
normX*=normX;
normY=norm(_y);
normY*=normY;
mulSpectrums(_xf,_yf,xyf,0,true);
pixelWiseMult(_xf,_yf,xyf_v,0,true);
sumChannels(xyf_v,xyf);
ifft2(xyf,xyf);
shiftRows(xyf, _x.rows/2);
shiftCols(xyf,_x.cols/2);
// shiftRows(xyf, _x.rows/2);
// shiftCols(xyf, _x.cols/2);
//(xx + yy - 2 * xy) / numel(x)
xy=(normX+normY-2*xyf)/(_x.rows*_x.cols);
xy=(normX+normY-2*xyf)/(_x.rows*_x.cols*_x.channels());
// TODO: check wether we really need thresholding or not
//threshold(xy,xy,0.0,0.0,THRESH_TOZERO);//max(0, (xx + yy - 2 * xy) / numel(x))
@@ -441,7 +488,7 @@ namespace cv{
}
/* CIRCULAR SHIT Function
/* CIRCULAR SHIFT Function
* http://stackoverflow.com/questions/10420454/shift-like-matlab-function-rows-or-columns-of-a-matrix-in-opencv
*/
// circular shift one row from up to down
@@ -523,16 +570,12 @@ namespace cv{
interp_factor=0.075;
output_sigma_factor=1.0/16.0;
resize=true;
max_patch_size=80*80;
descriptor=GRAY;
max_patch_size=100*100;
descriptor=CN;
}
void TrackerKCF::Params::read( const cv::FileNode& /*fn*/ ){
}
void TrackerKCF::Params::read( const cv::FileNode& /*fn*/ ){}
void TrackerKCF::Params::write( cv::FileStorage& /*fs*/ ) const{
}
void TrackerKCF::Params::write( cv::FileStorage& /*fs*/ ) const{}
} /* namespace cv */