refactored OpticalFlowDual_TVL1:

* added DenseOpticalFlow interface
* moved OpticalFlowDual_TVL1 to src folder

modules/gpu/perf/perf_video.cpp

@@ -431,13 +431,13 @@ PERF_TEST_P(ImagePair, Video_OpticalFlowDual_TVL1,
     {
         cv::Mat flow;
 
-        cv::OpticalFlowDual_TVL1 alg;
+        cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
 
-        alg(frame0, frame1, flow);
+        alg->calc(frame0, frame1, flow);
 
         TEST_CYCLE()
         {
-            alg(frame0, frame1, flow);
+            alg->calc(frame0, frame1, flow);
         }
 
         CPU_SANITY_CHECK(flow);

modules/gpu/test/test_optflow.cpp

@@ -431,9 +431,9 @@ GPU_TEST_P(OpticalFlowDual_TVL1, Accuracy)
     cv::gpu::GpuMat d_flowy = createMat(frame0.size(), CV_32FC1, useRoi);
     d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
 
-    cv::OpticalFlowDual_TVL1 alg;
+    cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
     cv::Mat flow;
-    alg(frame0, frame1, flow);
+    alg->calc(frame0, frame1, flow);
     cv::Mat gold[2];
     cv::split(flow, gold);
 

modules/video/doc/motion_analysis_and_object_tracking.rst

@@ -643,11 +643,11 @@ See [Tao2012]_. And site of project - http://graphics.berkeley.edu/papers/Tao-SA
 
 
 
-OpticalFlowDual_TVL1
---------------------
+createOptFlow_DualTVL1
+----------------------
 "Dual TV L1" Optical Flow Algorithm.
 
-.. ocv:class:: OpticalFlowDual_TVL12
+.. ocv:function:: Ptr<DenseOpticalFlow> createOptFlow_DualTVL1()
 
 
 The class implements the "Dual TV L1" optical flow algorithm described in [Zach2007]_ and [Javier2012]_ .
@@ -685,11 +685,11 @@ Here are important members of the class that control the algorithm, which you ca
 
 
 
-OpticalFlowDual_TVL1::operator()
---------------------------------
+DenseOpticalFlow::calc
+--------------------------
 Calculates an optical flow.
 
-.. ocv:function:: void OpticalFlowDual_TVL1::operator ()(InputArray I0, InputArray I1, InputOutputArray flow)
+.. ocv:function:: void DenseOpticalFlow::calc(InputArray I0, InputArray I1, InputOutputArray flow)
 
     :param prev: first 8-bit single-channel input image.
 
@@ -699,11 +699,11 @@ Calculates an optical flow.
 
 
 
-OpticalFlowDual_TVL1::collectGarbage
-------------------------------------
+DenseOpticalFlow::collectGarbage
+--------------------------------
 Releases all inner buffers.
 
-.. ocv:function:: void OpticalFlowDual_TVL1::collectGarbage()
+.. ocv:function:: void DenseOpticalFlow::collectGarbage()
 
 
 

modules/video/include/opencv2/video/tracking.hpp

@@ -352,104 +352,19 @@ CV_EXPORTS_W void calcOpticalFlowSF(Mat& from,
                                     double upscale_sigma_color,
                                     double speed_up_thr);
 
+class CV_EXPORTS DenseOpticalFlow : public Algorithm
+{
+public:
+    virtual void calc(InputArray I0, InputArray I1, InputOutputArray flow) = 0;
+    virtual void collectGarbage() = 0;
+};
+
 // Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method
 //
 // see reference:
 //   [1] C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow".
 //   [2] Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation".
-class CV_EXPORTS OpticalFlowDual_TVL1
-{
-public:
-    OpticalFlowDual_TVL1();
-
-    void operator ()(InputArray I0, InputArray I1, InputOutputArray flow);
-
-    void collectGarbage();
-
-    /**
-     * Time step of the numerical scheme.
-     */
-    double tau;
-
-    /**
-     * Weight parameter for the data term, attachment parameter.
-     * This is the most relevant parameter, which determines the smoothness of the output.
-     * The smaller this parameter is, the smoother the solutions we obtain.
-     * It depends on the range of motions of the images, so its value should be adapted to each image sequence.
-     */
-    double lambda;
-
-    /**
-     * Weight parameter for (u - v)^2, tightness parameter.
-     * It serves as a link between the attachment and the regularization terms.
-     * In theory, it should have a small value in order to maintain both parts in correspondence.
-     * The method is stable for a large range of values of this parameter.
-     */
-    double theta;
-
-    /**
-     * Number of scales used to create the pyramid of images.
-     */
-    int nscales;
-
-    /**
-     * Number of warpings per scale.
-     * Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale.
-     * This is a parameter that assures the stability of the method.
-     * It also affects the running time, so it is a compromise between speed and accuracy.
-     */
-    int warps;
-
-    /**
-     * Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time.
-     * A small value will yield more accurate solutions at the expense of a slower convergence.
-     */
-    double epsilon;
-
-    /**
-     * Stopping criterion iterations number used in the numerical scheme.
-     */
-    int iterations;
-
-    bool useInitialFlow;
-
-private:
-    void procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2);
-
-    std::vector<Mat_<float> > I0s;
-    std::vector<Mat_<float> > I1s;
-    std::vector<Mat_<float> > u1s;
-    std::vector<Mat_<float> > u2s;
-
-    Mat_<float> I1x_buf;
-    Mat_<float> I1y_buf;
-
-    Mat_<float> flowMap1_buf;
-    Mat_<float> flowMap2_buf;
-
-    Mat_<float> I1w_buf;
-    Mat_<float> I1wx_buf;
-    Mat_<float> I1wy_buf;
-
-    Mat_<float> grad_buf;
-    Mat_<float> rho_c_buf;
-
-    Mat_<float> v1_buf;
-    Mat_<float> v2_buf;
-
-    Mat_<float> p11_buf;
-    Mat_<float> p12_buf;
-    Mat_<float> p21_buf;
-    Mat_<float> p22_buf;
-
-    Mat_<float> div_p1_buf;
-    Mat_<float> div_p2_buf;
-
-    Mat_<float> u1x_buf;
-    Mat_<float> u1y_buf;
-    Mat_<float> u2x_buf;
-    Mat_<float> u2y_buf;
-};
+CV_EXPORTS Ptr<DenseOpticalFlow> createOptFlow_DualTVL1();
 
 }
 

modules/video/perf/perf_tvl1optflow.cpp

@@ -22,12 +22,9 @@ PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1, testing::Values(impair("cv/optflow/
 
     Mat flow;
 
-    OpticalFlowDual_TVL1 tvl1;
+    Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
 
-    TEST_CYCLE()
-    {
-        tvl1(frame1, frame2, flow);
-    }
+    TEST_CYCLE_N(10) tvl1->calc(frame1, frame2, flow);
 
     SANITY_CHECK(flow, 0.5);
 }

modules/video/test/test_tvl1optflow.cpp

@@ -152,9 +152,9 @@ TEST(Video_calcOpticalFlowDual_TVL1, Regression)
     ASSERT_FALSE(frame2.empty());
 
     Mat_<Point2f> flow;
-    OpticalFlowDual_TVL1 tvl1;
+    Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
 
-    tvl1(frame1, frame2, flow);
+    tvl1->calc(frame1, frame2, flow);
 
 #ifdef DUMP
     writeOpticalFlowToFile(flow, gold_flow_path);

samples/cpp/tvl1_optical_flow.cpp

@@ -173,10 +173,10 @@ int main(int argc, const char* argv[])
     }
 
     Mat_<Point2f> flow;
-    OpticalFlowDual_TVL1 tvl1;
+    Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
 
     const double start = (double)getTickCount();
-    tvl1(frame0, frame1, flow);
+    tvl1->calc(frame0, frame1, flow);
     const double timeSec = (getTickCount() - start) / getTickFrequency();
     cout << "calcOpticalFlowDual_TVL1 : " << timeSec << " sec" << endl;