由于opencv3的各种版本相对于opencv2的版本已经改变了很多内容，openTLD跟踪算法所依赖的一些函数在opencv3中已经消失了，为此需要对openTLD进行适当修改才能使之在opencv3的各种版本中运行。
加入如下文件，并在对应的地方include头文件即可。
PatchGenerator.h
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#include <opencv2/opencv.hpp>
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#ifndef PATCHGENERATOR_H
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#define <span style="font-family: Arial, Helvetica, sans-serif;">PATCHGENERATOR_H</span>
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namespace cv
- {
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class CV_EXPORTS PatchGenerator
- {
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public:
- PatchGenerator();
- PatchGenerator(double _backgroundMin, double _backgroundMax,
- double _noiseRange, bool _randomBlur=true,
- double _lambdaMin=0.6, double _lambdaMax=1.5,
- double _thetaMin=-CV_PI, double _thetaMax=CV_PI,
- double _phiMin=-CV_PI, double _phiMax=CV_PI );
- void operator()(const Mat& image, Point2f pt, Mat& patch, Size patchSize, RNG& rng) const;
- void operator()(const Mat& image, const Mat& transform, Mat& patch,
- Size patchSize, RNG& rng) const;
- void warpWholeImage(const Mat& image, Mat& matT, Mat& buf,
- CV_OUT Mat& warped, int border, RNG& rng) const;
- void generateRandomTransform(Point2f srcCenter, Point2f dstCenter,
- CV_OUT Mat& transform, RNG& rng,
- bool inverse=false) const;
- void setAffineParam(double lambda, double theta, double phi);
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- double backgroundMin, backgroundMax;
- double noiseRange;
- bool randomBlur;
- double lambdaMin, lambdaMax;
- double thetaMin, thetaMax;
- double phiMin, phiMax;
- };
- };
PatchGenerator.cpp
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#include <opencv2/opencv.hpp>
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#include <PatchGenerator.h>
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namespace cv
- {
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/*
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The code below implements keypoint detector, fern-based point classifier and a planar object detector.
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References:
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1. Mustafa Özuysal, Michael Calonder, Vincent Lepetit, Pascal Fua,
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"Fast KeyPoint Recognition Using Random Ferns,"
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 15 Jan. 2009.
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2. Vincent Lepetit, Pascal Fua,
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"Towards Recognizing Feature Points Using Classification Trees,"
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Technical Report IC/2004/74, EPFL, 2004.
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*/
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const int progressBarSize = 50;
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Patch Generator //
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static const double DEFAULT_BACKGROUND_MIN = 0;
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static const double DEFAULT_BACKGROUND_MAX = 256;
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static const double DEFAULT_NOISE_RANGE = 5;
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static const double DEFAULT_LAMBDA_MIN = 0.6;
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static const double DEFAULT_LAMBDA_MAX = 1.5;
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static const double DEFAULT_THETA_MIN = -CV_PI;
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static const double DEFAULT_THETA_MAX = CV_PI;
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static const double DEFAULT_PHI_MIN = -CV_PI;
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static const double DEFAULT_PHI_MAX = CV_PI;
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- PatchGenerator::PatchGenerator()
- : backgroundMin(DEFAULT_BACKGROUND_MIN), backgroundMax(DEFAULT_BACKGROUND_MAX),
- noiseRange(DEFAULT_NOISE_RANGE), randomBlur(true), lambdaMin(DEFAULT_LAMBDA_MIN),
- lambdaMax(DEFAULT_LAMBDA_MAX), thetaMin(DEFAULT_THETA_MIN),
- thetaMax(DEFAULT_THETA_MAX), phiMin(DEFAULT_PHI_MIN),
- phiMax(DEFAULT_PHI_MAX)
- {
- }
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- PatchGenerator::PatchGenerator(double _backgroundMin, double _backgroundMax,
- double _noiseRange, bool _randomBlur,
- double _lambdaMin, double _lambdaMax,
- double _thetaMin, double _thetaMax,
- double _phiMin, double _phiMax )
- : backgroundMin(_backgroundMin), backgroundMax(_backgroundMax),
- noiseRange(_noiseRange), randomBlur(_randomBlur),
- lambdaMin(_lambdaMin), lambdaMax(_lambdaMax),
- thetaMin(_thetaMin), thetaMax(_thetaMax),
- phiMin(_phiMin), phiMax(_phiMax)
- {
- }
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-
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void PatchGenerator::generateRandomTransform(Point2f srcCenter, Point2f dstCenter,
- Mat& transform, RNG& rng, bool inverse) const
- {
- double lambda1 = rng.uniform(lambdaMin, lambdaMax);
- double lambda2 = rng.uniform(lambdaMin, lambdaMax);
- double theta = rng.uniform(thetaMin, thetaMax);
- double phi = rng.uniform(phiMin, phiMax);
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- // Calculate random parameterized affine transformation A,
- // A = T(patch center) * R(theta) * R(phi)' *
- // S(lambda1, lambda2) * R(phi) * T(-pt)
- double st = sin(theta);
- double ct = cos(theta);
- double sp = sin(phi);
- double cp = cos(phi);
- double c2p = cp*cp;
- double s2p = sp*sp;
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- double A = lambda1*c2p + lambda2*s2p;
- double B = (lambda2 - lambda1)*sp*cp;
- double C = lambda1*s2p + lambda2*c2p;
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- double Ax_plus_By = A*srcCenter.x + B*srcCenter.y;
- double Bx_plus_Cy = B*srcCenter.x + C*srcCenter.y;
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- transform.create(2, 3, CV_64F);
- Mat_<double>& T = (Mat_<double>&)transform;
- T(0,0) = A*ct - B*st;
- T(0,1) = B*ct - C*st;
- T(0,2) = -ct*Ax_plus_By + st*Bx_plus_Cy + dstCenter.x;
- T(1,0) = A*st + B*ct;
- T(1,1) = B*st + C*ct;
- T(1,2) = -st*Ax_plus_By - ct*Bx_plus_Cy + dstCenter.y;
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- if( inverse )
- invertAffineTransform(T, T);
- }
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void PatchGenerator::operator ()(const Mat& image, Point2f pt, Mat& patch, Size patchSize, RNG& rng) const
- {
- double buffer[6];
- Mat_<double> T(2, 3, buffer);
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- generateRandomTransform(pt, Point2f((patchSize.width-1)*0.5f, (patchSize.height-1)*0.5f), T, rng);
- (*this)(image, T, patch, patchSize, rng);
- }
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void PatchGenerator::operator ()(const Mat& image, const Mat& T,
- Mat& patch, Size patchSize, RNG& rng) const
- {
- patch.create( patchSize, image.type() );
- if( backgroundMin != backgroundMax )
- {
- rng.fill(patch, RNG::UNIFORM, Scalar::all(backgroundMin), Scalar::all(backgroundMax));
- warpAffine(image, patch, T, patchSize, INTER_LINEAR, BORDER_TRANSPARENT);
- }
- else
- warpAffine(image, patch, T, patchSize, INTER_LINEAR, BORDER_CONSTANT, Scalar::all(backgroundMin));
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- int ksize = randomBlur ? (unsigned)rng % 9 - 5 : 0;
- if( ksize > 0 )
- {
- ksize = ksize*2 + 1;
- GaussianBlur(patch, patch, Size(ksize, ksize), 0, 0);
- }
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- if( noiseRange > 0 )
- {
- AutoBuffer<uchar> _noiseBuf( patchSize.width*patchSize.height*image.elemSize() );
- Mat noise(patchSize, image.type(), (uchar*)_noiseBuf);
- int delta = image.depth() == CV_8U ? 128 : image.depth() == CV_16U ? 32768 : 0;
- rng.fill(noise, RNG::NORMAL, Scalar::all(delta), Scalar::all(noiseRange));
- if( backgroundMin != backgroundMax )
- addWeighted(patch, 1, noise, 1, -delta, patch);
- else
- {
- for( int i = 0; i < patchSize.height; i++ )
- {
- uchar* prow = patch.ptr<uchar>(i);
- const uchar* nrow = noise.ptr<uchar>(i);
- for( int j = 0; j < patchSize.width; j++ )
- if( prow[j] != backgroundMin )
- prow[j] = saturate_cast<uchar>(prow[j] + nrow[j] - delta);
- }
- }
- }
- }
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void PatchGenerator::warpWholeImage(const Mat& image, Mat& matT, Mat& buf,
- Mat& warped, int border, RNG& rng) const
- {
- Mat_<double> T = matT;
- Rect roi(INT_MAX, INT_MAX, INT_MIN, INT_MIN);
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- for( int k = 0; k < 4; k++ )
- {
- Point2f pt0, pt1;
- pt0.x = (float)(k == 0 || k == 3 ? 0 : image.cols);
- pt0.y = (float)(k < 2 ? 0 : image.rows);
- pt1.x = (float)(T(0,0)*pt0.x + T(0,1)*pt0.y + T(0,2));
- pt1.y = (float)(T(1,0)*pt0.x + T(1,1)*pt0.y + T(1,2));
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- roi.x = std::min(roi.x, cvFloor(pt1.x));
- roi.y = std::min(roi.y, cvFloor(pt1.y));
- roi.width = std::max(roi.width, cvCeil(pt1.x));
- roi.height = std::max(roi.height, cvCeil(pt1.y));
- }
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- roi.width -= roi.x - 1;
- roi.height -= roi.y - 1;
- int dx = border - roi.x;
- int dy = border - roi.y;
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- if( (roi.width+border*2)*(roi.height+border*2) > buf.cols )
- buf.create(1, (roi.width+border*2)*(roi.height+border*2), image.type());
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- warped = Mat(roi.height + border*2, roi.width + border*2,
- image.type(), buf.data);
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- T(0,2) += dx;
- T(1,2) += dy;
- (*this)(image, T, warped, warped.size(), rng);
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- if( T.data != matT.data )
- T.convertTo(matT, matT.type());
- }
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// Params are assumed to be symmetrical: lambda w.r.t. 1, theta and phi w.r.t. 0
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void PatchGenerator::setAffineParam(double lambda, double theta, double phi)
- {
- lambdaMin = 1. - lambda;
- lambdaMax = 1. + lambda;
- thetaMin = -theta;
- thetaMax = theta;
- phiMin = -phi;
- phiMax = phi;
- }
- };
原文 http://blog.csdn.net/j10527/article/details/51305087
