Added flow estimation using DCT basis

modules/optflow/include/opencv2/optflow.hpp

@@ -43,6 +43,8 @@ the use of this software, even if advised of the possibility of such damage.
 #include "opencv2/core.hpp"
 #include "opencv2/video.hpp"
 
+#include "opencv2/optflow/pcaflow.hpp"
+
 /**
 @defgroup optflow Optical Flow Algorithms
 
@@ -193,8 +195,6 @@ CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_SparseToDense();
 
 CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_BlockMatching();
 
-CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_PCAFlow();
-
 //! @}
 
 } //optflow

modules/optflow/include/opencv2/optflow/pcaflow.hpp

+/*
+By downloading, copying, installing or using the software you agree to this
+license. If you do not agree to this license, do not download, install,
+copy or use the software.
+
+
+                          License Agreement
+               For Open Source Computer Vision Library
+                       (3-clause BSD License)
+
+Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+Third party copyrights are property of their respective owners.
+
+Redistribution and use in source and binary forms, with or without modification,
+are permitted provided that the following conditions are met:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions in binary form must reproduce the above copyright notice,
+    this list of conditions and the following disclaimer in the documentation
+    and/or other materials provided with the distribution.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may be used to endorse or promote products derived from this software
+    without specific prior written permission.
+
+This software is provided by the copyright holders and contributors "as is" and
+any express or implied warranties, including, but not limited to, the implied
+warranties of merchantability and fitness for a particular purpose are
+disclaimed. In no event shall copyright holders or contributors be liable for
+any direct, indirect, incidental, special, exemplary, or consequential damages
+(including, but not limited to, procurement of substitute goods or services;
+loss of use, data, or profits; or business interruption) however caused
+and on any theory of liability, whether in contract, strict liability,
+or tort (including negligence or otherwise) arising in any way out of
+the use of this software, even if advised of the possibility of such damage.
+*/
+
+#ifndef __OPENCV_OPTFLOW_PCAFLOW_HPP__
+#define __OPENCV_OPTFLOW_PCAFLOW_HPP__
+
+#include "opencv2/core.hpp"
+#include "opencv2/video.hpp"
+
+namespace cv
+{
+namespace optflow
+{
+
+class OpticalFlowPCAFlow : public DenseOpticalFlow
+{
+protected:
+  const Size basisSize;
+  const float sparseRate;              // (0 .. 0.1)
+  const float retainedCornersFraction; // [0 .. 1]
+  const float occlusionsThreshold;
+
+public:
+  OpticalFlowPCAFlow( Size _basisSize = Size( 18, 14 ), float _sparseRate = 0.02, float _retainedCornersFraction = 1.0,
+                      float _occlusionsThreshold = 0.00002 );
+
+  void calc( InputArray I0, InputArray I1, InputOutputArray flow );
+  void collectGarbage();
+
+private:
+  void findSparseFeatures( Mat &from, Mat &to, std::vector<Point2f> &features,
+                           std::vector<Point2f> &predictedFeatures ) const;
+
+  void removeOcclusions( Mat &from, Mat &to, std::vector<Point2f> &features,
+                         std::vector<Point2f> &predictedFeatures ) const;
+
+  void getSystem( OutputArray AOut, OutputArray b1Out, OutputArray b2Out, const std::vector<Point2f> &features,
+                  const std::vector<Point2f> &predictedFeatures, const Size size );
+};
+
+CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_PCAFlow();
+}
+}
+
+#endif

modules/optflow/src/pcaflow.cpp

@@ -41,31 +41,50 @@
  //M*/
 
 #include "precomp.hpp"
+//#include <iostream>
+// using std::cout;
+// using std::endl;
 
 namespace cv
 {
 namespace optflow
 {
 
-class OpticalFlowPCAFlow : public DenseOpticalFlow
+OpticalFlowPCAFlow::OpticalFlowPCAFlow( Size _basisSize, float _sparseRate, float _retainedCornersFraction,
+                                        float _occlusionsThreshold )
+    : basisSize( _basisSize ), sparseRate( _sparseRate ), retainedCornersFraction( _retainedCornersFraction ),
+      occlusionsThreshold( _occlusionsThreshold )
 {
-protected:
-  float sparseRate;
-
-public:
-  OpticalFlowPCAFlow() : sparseRate( 0.02 ){};
+  CV_Assert( sparseRate > 0 && sparseRate <= 0.1 );
+  CV_Assert( retainedCornersFraction >= 0 && retainedCornersFraction <= 1.0 );
+  CV_Assert( occlusionsThreshold > 0 );
+}
 
-  void calc( InputArray I0, InputArray I1, InputOutputArray flow );
-  void collectGarbage();
+inline float eDistSq( const Point2f &p1, const Point2f &p2 )
+{
+  const float dx = p1.x - p2.x;
+  const float dy = p1.y - p2.y;
+  return dx * dx + dy * dy;
+}
 
-private:
-  void findSparseFeatures( Mat &from, Mat &to, std::vector<Point2f> &features,
-                           std::vector<Point2f> &predictedFeatures );
-};
+inline float eNormSq( const Point2f &v ) { return v.x * v.x + v.y * v.y; }
 
 void OpticalFlowPCAFlow::findSparseFeatures( Mat &from, Mat &to, std::vector<Point2f> &features,
-                                             std::vector<Point2f> &predictedFeatures )
+                                             std::vector<Point2f> &predictedFeatures ) const
 {
+  Size size = from.size();
+  const unsigned maxFeatures = size.area() * sparseRate;
+  goodFeaturesToTrack( from, features, maxFeatures * retainedCornersFraction, 0.005, 3 );
+
+  // Add points along the grid if not enough features
+  if ( maxFeatures > features.size() )
+  {
+    const unsigned missingPoints = maxFeatures - features.size();
+    const unsigned blockSize = sqrt( (float)size.area() / missingPoints );
+    for ( int x = blockSize / 2; x < size.width; x += blockSize )
+      for ( int y = blockSize / 2; y < size.height; y += blockSize )
+        features.push_back( Point2f( x, y ) );
+  }
   std::vector<uchar> predictedStatus;
   std::vector<float> predictedError;
   calcOpticalFlowPyrLK( from, to, features, predictedFeatures, predictedStatus, predictedError );
@@ -84,11 +103,204 @@ void OpticalFlowPCAFlow::findSparseFeatures( Mat &from, Mat &to, std::vector<Poi
   predictedFeatures.resize( j );
 }
 
-void OpticalFlowPCAFlow::calc( InputArray I0, InputArray I1, InputOutputArray flow_out )
+void OpticalFlowPCAFlow::removeOcclusions( Mat &from, Mat &to, std::vector<Point2f> &features,
+                                           std::vector<Point2f> &predictedFeatures ) const
+{
+  std::vector<uchar> predictedStatus;
+  std::vector<float> predictedError;
+  std::vector<Point2f> backwardFeatures;
+  calcOpticalFlowPyrLK( to, from, predictedFeatures, backwardFeatures, predictedStatus, predictedError );
+
+  size_t j = 0;
+  const float threshold = occlusionsThreshold * from.size().area();
+  for ( size_t i = 0; i < predictedFeatures.size(); ++i )
+  {
+    if ( predictedStatus[i] )
+    {
+      Point2f flowDiff = features[i] - backwardFeatures[i];
+      if ( eNormSq( flowDiff ) < threshold )
+      {
+        features[j] = features[i];
+        predictedFeatures[j] = predictedFeatures[i];
+        ++j;
+      }
+    }
+  }
+  features.resize( j );
+  predictedFeatures.resize( j );
+}
+
+void OpticalFlowPCAFlow::getSystem( OutputArray AOut, OutputArray b1Out, OutputArray b2Out,
+                                    const std::vector<Point2f> &features, const std::vector<Point2f> &predictedFeatures,
+                                    const Size size )
+{
+  AOut.create( features.size(), basisSize.area(), CV_32F );
+  b1Out.create( features.size(), 1, CV_32F );
+  b2Out.create( features.size(), 1, CV_32F );
+  Mat A = AOut.getMat();
+  Mat b1 = b1Out.getMat();
+  Mat b2 = b2Out.getMat();
+  const Point2f scale =
+    Point2f( (float)basisSize.width / (float)size.width, (float)basisSize.height / (float)size.height );
+  for ( size_t i = 0; i < features.size(); ++i )
+  {
+    const Point2f p = Point2f( features[i].x * scale.x, features[i].y * scale.y );
+    for ( int n1 = 0; n1 < basisSize.width; ++n1 )
+      for ( int n2 = 0; n2 < basisSize.height; ++n2 )
+      {
+        const float c = cos( ( n1 * M_PI / basisSize.width ) * ( p.x + 0.5 ) ) *
+                        cos( ( n2 * M_PI / basisSize.height ) * ( p.y + 0.5 ) );
+        A.at<float>( i, n1 * basisSize.height + n2 ) = c;
+      }
+    const Point2f flow = predictedFeatures[i] - features[i];
+    b1.at<float>( i ) = flow.x;
+    b2.at<float>( i ) = flow.y;
+  }
+}
+
+template <typename T> static inline int mathSign( T val ) { return ( T( 0 ) < val ) - ( val < T( 0 ) ); }
+
+static inline void symOrtho( double a, double b, double &c, double &s, double &r )
+{
+  if ( b == 0 )
+  {
+    c = mathSign( a );
+    s = 0;
+    r = std::abs( a );
+  }
+  else if ( a == 0 )
+  {
+    c = 0;
+    s = mathSign( b );
+    r = std::abs( b );
+  }
+  else if ( std::abs( b ) > std::abs( a ) )
+  {
+    const double tau = a / b;
+    s = mathSign( b ) / sqrt( 1 + tau * tau );
+    c = s * tau;
+    r = b / s;
+  }
+  else
+  {
+    const double tau = b / a;
+    c = mathSign( a ) / sqrt( 1 + tau * tau );
+    s = c * tau;
+    r = a / c;
+  }
+}
+
+static void solveLSQR( const Mat &A, const Mat &b, OutputArray xOut, const double damp = 0.0,
+                       const unsigned iter_lim = 10 )
+{
+  int m = A.size().height;
+  int n = A.size().width;
+  CV_Assert( m == b.size().height );
+  CV_Assert( A.type() == CV_32F );
+  CV_Assert( b.type() == CV_32F );
+  xOut.create( n, 1, CV_32F );
+
+  double anorm = 0;
+  const double dampsq = damp * damp;
+  double ddnorm = 0;
+  double res2 = 0;
+  double xxnorm = 0;
+  double z = 0;
+  double cs2 = -1;
+  double sn2 = 0;
+
+  Mat v( n, 1, CV_32F, 0.0f );
+  Mat u = b;
+  Mat x = xOut.getMat();
+  x = Mat::zeros( x.size(), x.type() );
+  double alfa = 0;
+  double beta = cv::norm( u, NORM_L2 );
+  Mat w( n, 1, CV_32F, 0.0f );
+
+  if ( beta > 0 )
+  {
+    u *= 1 / beta;
+    v = A.t() * u;
+    alfa = cv::norm( v, NORM_L2 );
+  }
+
+  if ( alfa > 0 )
+  {
+    v *= 1 / alfa;
+    w = v.clone();
+  }
+
+  double rhobar = alfa;
+  double phibar = beta;
+  double rnorm = beta;
+  double r1norm = rnorm;
+  double arnorm = alfa * beta;
+  if ( arnorm == 0 )
+    return;
+
+  for ( unsigned itn = 0; itn < iter_lim; ++itn )
+  {
+    u = A * v - alfa * u;
+    beta = cv::norm( u, NORM_L2 );
+
+    if ( beta > 0 )
+    {
+      u *= 1 / beta;
+      anorm = sqrt( anorm * anorm + alfa * alfa + beta * beta + damp * damp );
+      v = A.t() * u - beta * v;
+      alfa = cv::norm( v, NORM_L2 );
+      if ( alfa > 0 )
+        v = ( 1 / alfa ) * v;
+    }
+
+    double rhobar1 = sqrt( rhobar * rhobar + damp * damp );
+    double cs1 = rhobar / rhobar1;
+    double sn1 = damp / rhobar1;
+    double psi = sn1 * phibar;
+    phibar = cs1 * phibar;
+
+    double cs, sn, rho;
+    symOrtho( rhobar1, beta, cs, sn, rho );
+
+    double theta = sn * alfa;
+    rhobar = -cs * alfa;
+    double phi = cs * phibar;
+    phibar = sn * phibar;
+    double tau = sn * phi;
+
+    double t1 = phi / rho;
+    double t2 = -theta / rho;
+    Mat dk = ( 1 / rho ) * w;
+
+    x = x + t1 * w;
+    w = v + t2 * w;
+    ddnorm += cv::norm( dk, NORM_L2SQR );
+
+    double delta = sn2 * rho;
+    double gambar = -cs2 * rho;
+    double rhs = phi - delta * z;
+    double gamma = sqrt( gambar * gambar + theta * theta );
+    cs2 = gambar / gamma;
+    sn2 = theta / gamma;
+    z = rhs / gamma;
+    xxnorm = xxnorm + z * z;
+
+    double res1 = phibar * phibar;
+    res2 = res2 + psi * psi;
+    rnorm = sqrt( res1 + res2 );
+    arnorm = alfa * std::abs( tau );
+
+    double r1sq = rnorm * rnorm - dampsq * xxnorm;
+    r1norm = sqrt( std::abs( r1sq ) );
+    if ( r1sq < 0 )
+      r1norm = -r1norm;
+  }
+}
+
+void OpticalFlowPCAFlow::calc( InputArray I0, InputArray I1, InputOutputArray flowOut )
 {
-  Size size = I0.size();
+  const Size size = I0.size();
   CV_Assert( size == I1.size() );
-  CV_Assert( sparseRate > 0 && sparseRate < 0.1 );
 
   Mat from, to;
   if ( I0.channels() == 3 )
@@ -114,31 +326,40 @@ void OpticalFlowPCAFlow::calc( InputArray I0, InputArray I1, InputOutputArray fl
   CV_Assert( to.channels() == 1 );
 
   std::vector<Point2f> features, predictedFeatures;
-  const unsigned maxFeatures = size.area() * sparseRate;
-  goodFeaturesToTrack( from, features, maxFeatures, 0.005, 3 );
-
-  // Add points along the grid if not enough features
-  {
-    const unsigned missingPoints = maxFeatures - features.size();
-    const unsigned blockSize = sqrt( (float)size.area() / missingPoints );
-    for ( int x = blockSize / 2; x < size.width; x += blockSize )
-      for ( int y = blockSize / 2; y < size.height; y += blockSize )
-        features.push_back( Point2f( x, y ) );
-  }
-
   findSparseFeatures( from, to, features, predictedFeatures );
+  removeOcclusions( from, to, features, predictedFeatures );
 
-  // TODO: Remove occlusions
+  // from.convertTo( from, CV_32F );
+  // to.convertTo( to, CV_32F );
 
-  flow_out.create( size, CV_32FC2 );
-  Mat flow = flow_out.getMat();
-  for ( size_t i = 0; i < features.size(); ++i )
+  flowOut.create( size, CV_32FC2 );
+  Mat flow = flowOut.getMat();
+  // interpolateSparseFlow(flow, features, predictedFeatures);
+  // for ( size_t i = 0; i < features.size(); ++i )
+  //  flow.at<Point2f>( features[i].y, features[i].x ) = /*Point2f(10,10);*/ predictedFeatures[i] - features[i];
+
+  Mat A, b1, b2, w1, w2;
+  getSystem( A, b1, b2, features, predictedFeatures, size );
+  // solve( A, b1, w1, DECOMP_CHOLESKY | DECOMP_NORMAL );
+  // solve( A, b2, w2, DECOMP_CHOLESKY | DECOMP_NORMAL );
+  solveLSQR( A, b1, w1, 2 );
+  solveLSQR( A, b2, w2, 2 );
+  Mat flowSmall( basisSize, CV_32FC2 );
+  for ( int y = 0; y < basisSize.height; ++y )
+    for ( int x = 0; x < basisSize.width; ++x )
     {
-    flow.at<Point2f>( features[i].y, features[i].x ) = predictedFeatures[i] - features[i];
+      float sumX = 0, sumY = 0;
+      for ( int n1 = 0; n1 < basisSize.width; ++n1 )
+        for ( int n2 = 0; n2 < basisSize.height; ++n2 )
+        {
+          const float c = cos( ( n1 * M_PI / basisSize.width ) * ( x + 0.5 ) ) *
+                          cos( ( n2 * M_PI / basisSize.height ) * ( y + 0.5 ) );
+          sumX += c * w1.at<float>( n1 * basisSize.height + n2 );
+          sumY += c * w2.at<float>( n1 * basisSize.height + n2 );
         }
-
-  from.convertTo( from, CV_32F );
-  to.convertTo( to, CV_32F );
+      flowSmall.at<Point2f>( y, x ) = Point2f( sumX, sumY );
+    }
+  resize( flowSmall, flow, size, 0, 0, INTER_CUBIC );
 }
 
 void OpticalFlowPCAFlow::collectGarbage() {}