tracking: update tresholds in regression tests of the TLD

modules/tracking/src/multiTracker.cpp

@@ -408,7 +408,7 @@ namespace cv
 				////To fix: Check the paper, probably this cause wrong learning
 				//
 				labPatch.isObject = srValue > tld::THETA_NN;
-				labPatch.shouldBeIntegrated = abs(srValue - tld::THETA_NN) < 0.1;
+                labPatch.shouldBeIntegrated = abs(srValue - tld::THETA_NN) < tld::CLASSIFIER_MARGIN;
 				patches[k].push_back(labPatch);
 				//
 

modules/tracking/src/tldDetector.cpp

@@ -420,7 +420,7 @@ namespace cv
 				////To fix: Check the paper, probably this cause wrong learning
 				//
 				labPatch.isObject = srValue > THETA_NN;
-				labPatch.shouldBeIntegrated = abs(srValue - THETA_NN) < 0.1;
+                labPatch.shouldBeIntegrated = abs(srValue - THETA_NN) < CLASSIFIER_MARGIN;
 				patches.push_back(labPatch);
 				//
 
@@ -539,7 +539,7 @@ namespace cv
 				////To fix: Check the paper, probably this cause wrong learning
 				//
 				labPatch.isObject = srValue > THETA_NN;
-				labPatch.shouldBeIntegrated = abs(srValue - THETA_NN) < 0.1;
+                labPatch.shouldBeIntegrated = abs(srValue - THETA_NN) < CLASSIFIER_MARGIN;
 				patches.push_back(labPatch);
 				//
 

modules/tracking/src/tldDetector.hpp

@@ -57,8 +57,9 @@ namespace cv
 		const int MEASURES_PER_CLASSIFIER = 13;
 		const int GRIDSIZE = 15;
 		const int DOWNSCALE_MODE = cv::INTER_LINEAR;
-		const double THETA_NN = 0.50;
+        const double THETA_NN = 0.5;
 		const double CORE_THRESHOLD = 0.5;
+        const double CLASSIFIER_MARGIN = 0.1;
 		const double SCALE_STEP = 1.2;
 		const double ENSEMBLE_THRESHOLD = 0.5;
 		const double VARIANCE_THRESHOLD = 0.5;

modules/tracking/src/tldTracker.cpp

@@ -262,9 +262,9 @@ int TrackerTLDImpl::Pexpert::additionalExamples(std::vector<Mat_<uchar> >& examp
     TLDDetector::generateScanGrid(img_.rows, img_.cols, initSize_, scanGrid);
     getClosestN(scanGrid, Rect2d(resultBox_.x / scale, resultBox_.y / scale, resultBox_.width / scale, resultBox_.height / scale), 10, closest);
 
-    for( int i = 0; i < (int)closest.size(); i++ )
+    for( size_t i = 0; i < closest.size(); i++ )
     {
-        for( int j = 0; j < 10; j++ )
+        for( size_t j = 0; j < 10; j++ )
         {
             Point2f center;
             Size2f size;

modules/tracking/src/tldUtils.cpp

@@ -151,16 +151,11 @@ void getClosestN(std::vector<Rect2d>& scanGrid, Rect2d bBox, int n, std::vector<
 double variance(const Mat& img)
 {
     double p = 0, p2 = 0;
-    for( int i = 0; i < img.rows; i++ )
-    {
-        for( int j = 0; j < img.cols; j++ )
-        {
-            p += img.at<uchar>(i, j);
-            p2 += img.at<uchar>(i, j) * img.at<uchar>(i, j);
-        }
-    }
+    p = sum(img)(0);
+    p2 = norm(img, NORM_L2SQR);
     p /= (img.cols * img.rows);
     p2 /= (img.cols * img.rows);
+
     return p2 - p * p;
 }
 

modules/tracking/test/test_trackers.cpp

@@ -461,7 +461,7 @@ TEST_P(DistanceAndOverlap, KCF)
 
 TEST_P(DistanceAndOverlap, TLD)
 {
-  TrackerTest test( TrackerTLD::create(), dataset, 60, .4f, NoTransform);
+  TrackerTest test( TrackerTLD::create(), dataset, 40, .45f, NoTransform);
   test.run();
 }
 /***************************************************************************************/
@@ -492,7 +492,7 @@ TEST_P(DistanceAndOverlap, Shifted_Data_KCF)
 
 TEST_P(DistanceAndOverlap, Shifted_Data_TLD)
 {
-  TrackerTest test( TrackerTLD::create(), dataset, 120, .2f, CenterShiftLeft);
+  TrackerTest test( TrackerTLD::create(), dataset, 30, .35f, CenterShiftLeft);
   test.run();
 }
 /***************************************************************************************/
@@ -523,7 +523,7 @@ TEST_P(DistanceAndOverlap, Scaled_Data_KCF)
 
 TEST_P(DistanceAndOverlap, Scaled_Data_TLD)
 {
-  TrackerTest test( TrackerTLD::create(), dataset, 120, .45f, Scale_1_1);
+  TrackerTest test( TrackerTLD::create(), dataset, 30, .45f, Scale_1_1);
   test.run();
 }