remove global ArUco3 params (threshold)

Author: AleksandrPanov

modules/aruco/include/opencv2/aruco.hpp

@@ -163,17 +163,7 @@ enum CornerRefineMethod{
  *   Latter is the binarized image in which contours are searched.
  *   So all contours with a size smaller than minSideLengthCanonicalImg*minSideLengthCanonicalImg will omitted from the search.
  * - minMarkerLengthRatioOriginalImg:  range [0,1], eq (2) from paper
- * - cameraMotionSpeed: is in the range [0,1]. This parameter (tau_s in the paper) implements the feature proposed
- *   in Section 3.7. and is particularly useful for video sequences.
- *   The parameter tau_i has a direct influence on the processing speed. Instead of setting a fixed value for it,
- *   it can be adjusted at the end of each frame using
- *   tau_i = (1-tau_s)*P(v_s)/4 (eq. 6 in paper).
- *   Where P(v_s) is the perimeter of the smallest marker that was detected in the last frame.
- * - useGlobalThreshold: if we process a video, the assumption is, that the illumination conditions remains
- *   constant and global instead of adaptive thresholding can be applied, speeding up the binarization step.
- * - foundGlobalThreshold: internal variable. It is used to cache the variable to the next detector call.
- * - otsuGlobalThreshold: internal variable. It is used to cache the global otsu threshold to the next detector call.
- * - foundMarkerInLastFrames: internal variable. It is used to cache if markers were found in the last frame.
+ *   The parameter tau_i has a direct influence on the processing speed.
  */
 struct CV_EXPORTS_W DetectorParameters {
 
@@ -222,13 +212,6 @@ struct CV_EXPORTS_W DetectorParameters {
     CV_PROP_RW bool useAruco3Detection;
     CV_PROP_RW int minSideLengthCanonicalImg;
     CV_PROP_RW float minMarkerLengthRatioOriginalImg;
-
-    // New Aruco functionality especially for video
-    CV_PROP_RW float cameraMotionSpeed;
-    CV_PROP_RW bool useGlobalThreshold;
-    CV_PROP_RW bool foundGlobalThreshold;
-    CV_PROP_RW float otsuGlobalThreshold;
-    CV_PROP_RW int foundMarkerInLastFrames;
 };
 
 
@@ -256,13 +239,12 @@ struct CV_EXPORTS_W DetectorParameters {
  * are searched. For each detected marker, it returns the 2D position of its corner in the image
  * and its corresponding identifier.
  * Note that this function does not perform pose estimation.
- * The function returns an estimate of the parameter minMarkerLengthRatioOriginalImg if useAruco3Detection=1. If not it returns 0.0.
- * @sa estimatePoseSingleMarkers, estimatePoseBoard
+ * @sa estimatePoseSingleMarkers,  estimatePoseBoard
  *
  */
-CV_EXPORTS_W float detectMarkers(InputArray image, const Ptr<Dictionary> &dictionary, OutputArrayOfArrays corners,
-                                 OutputArray ids, const Ptr<DetectorParameters> &parameters = DetectorParameters::create(),
-                                 OutputArrayOfArrays rejectedImgPoints = noArray(), InputArray cameraMatrix= noArray(), InputArray distCoeff= noArray());
+CV_EXPORTS_W void detectMarkers(InputArray image, const Ptr<Dictionary> &dictionary, OutputArrayOfArrays corners,
+                                OutputArray ids, const Ptr<DetectorParameters> &parameters = DetectorParameters::create(),
+                                OutputArrayOfArrays rejectedImgPoints = noArray(), InputArray cameraMatrix= noArray(), InputArray distCoeff= noArray());
 
 
 

modules/aruco/perf/perf_aruco.cpp

@@ -155,16 +155,22 @@ class MarkerPainter
 static inline double getMaxDistance(map<int, vector<Point2f> > &golds, const vector<int>& ids,
                                                const vector<vector<Point2f> >& corners)
 {
-    double distance = 0.;
+    std::map<int, double> mapDist;
+    for (const auto& el : golds)
+        mapDist[el.first] = std::numeric_limits<double>::max();
     for (size_t i = 0; i < ids.size(); i++)
     {
         int id = ids[i];
         const auto gold_corners = golds.find(id);
-        if (gold_corners != golds.end())
-        for (int c = 0; c < 4; c++)
-            distance = std::max(distance, cv::norm(gold_corners->second[c] - corners[i][c]));
+        if (gold_corners != golds.end()) {
+            double distance = 0.;
+            for (int c = 0; c < 4; c++)
+                distance = std::max(distance, cv::norm(gold_corners->second[c] - corners[i][c]));
+            mapDist[id] = distance;
+        }
     }
-    return distance;
+    return std::max_element(std::begin(mapDist), std::end(mapDist),
+           [](const pair<int, double>& p1, const pair<int, double>& p2){return p1.second < p2.second;})->second;
 }
 
 PERF_TEST_P(EstimateAruco, ArucoFirst, ESTIMATE_PARAMS)
@@ -190,7 +196,7 @@ PERF_TEST_P(EstimateAruco, ArucoFirst, ESTIMATE_PARAMS)
     // detect markers
     vector<vector<Point2f> > corners;
     vector<int> ids;
-    TEST_CYCLE_N(10)
+    TEST_CYCLE()
     {
         aruco::detectMarkers(image_map.first, dictionary, corners, ids, detectorParams);
     }
@@ -223,7 +229,7 @@ PERF_TEST_P(EstimateAruco, ArucoSecond, ESTIMATE_PARAMS)
     // detect markers
     vector<vector<Point2f> > corners;
     vector<int> ids;
-    TEST_CYCLE_N(10)
+    TEST_CYCLE()
     {
         aruco::detectMarkers(image_map.first, dictionary, corners, ids, detectorParams);
     }
@@ -278,7 +284,7 @@ PERF_TEST_P(EstimateLargeAruco, ArucoFHD, ESTIMATE_FHD_PARAMS)
     // detect markers
     vector<vector<Point2f> > corners;
     vector<int> ids;
-    TEST_CYCLE_N(10)
+    TEST_CYCLE()
     {
         aruco::detectMarkers(image_map.first, dictionary, corners, ids, detectorParams);
     }
@@ -288,4 +294,4 @@ PERF_TEST_P(EstimateLargeAruco, ArucoFHD, ESTIMATE_FHD_PARAMS)
     SANITY_CHECK_NOTHING();
 }
 
-}
+}

modules/aruco/samples/detect_markers.cpp

@@ -63,8 +63,7 @@ const char* keys  =
         "{dp       |       | File of marker detector parameters }"
         "{r        |       | show rejected candidates too }"
         "{refine   |       | Corner refinement: CORNER_REFINE_NONE=0, CORNER_REFINE_SUBPIX=1,"
-        "CORNER_REFINE_CONTOUR=2, CORNER_REFINE_APRILTAG=3}"
-        "{ar3vid   |       | Adapt the paramater tau_i if aruco3 functionality is used. }";
+        "CORNER_REFINE_CONTOUR=2, CORNER_REFINE_APRILTAG=3}";
 }
 //! [aruco_detect_markers_keys]
 
@@ -80,7 +79,6 @@ int main(int argc, char *argv[]) {
     bool showRejected = parser.has("r");
     bool estimatePose = parser.has("c");
     float markerLength = parser.get<float>("l");
-    bool useAruco3DynamicUpdates = parser.has("ar3vid");
 
     Ptr<aruco::DetectorParameters> detectorParams;
     if(parser.has("dp")) {
@@ -141,7 +139,7 @@ int main(int argc, char *argv[]) {
     int waitTime;
     if(!video.empty()) {
         inputVideo.open(video);
-        waitTime = 1;
+        waitTime = 0;
     } else {
         inputVideo.open(camId);
         waitTime = 10;
@@ -150,8 +148,6 @@ int main(int argc, char *argv[]) {
     double totalTime = 0;
     int totalIterations = 0;
 
-    float new_marker_length_ratio = 0.0;
-    size_t total_nr_detected_corners = 0;
     while(inputVideo.grab()) {
         Mat image, imageCopy;
         inputVideo.retrieve(image);
@@ -163,16 +159,7 @@ int main(int argc, char *argv[]) {
         vector< Vec3d > rvecs, tvecs;
 
         // detect markers and estimate pose
-        if (useAruco3DynamicUpdates) {
-            // if new aruco3 features are used, we can also set the new min
-            // marker length ratio dymamically from the last frame
-            detectorParams->minMarkerLengthRatioOriginalImg = new_marker_length_ratio;
-            if(totalIterations % 30 == 0) {
-                cout<<"Current tau_i= "<<new_marker_length_ratio<<"\n";
-            }
-        }
-        new_marker_length_ratio = aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);
-        total_nr_detected_corners += ids.size();
+        aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);
         if(estimatePose && ids.size() > 0)
             aruco::estimatePoseSingleMarkers(corners, markerLength, camMatrix, distCoeffs, rvecs,
                                              tvecs);

modules/aruco/samples/detector_params.yml

@@ -22,7 +22,7 @@ maxErroneousBitsInBorderRate: 0.04
 minOtsuStdDev: 5.0
 errorCorrectionRate: 0.6
 
-# new aruco functionality
+# new aruco 3 functionality
 useAruco3Detection: 0
 minSideLengthCanonicalImg: 32 # 16, 32, 64 --> tau_c from the paper
 minMarkerLengthRatioOriginalImg: 0.02 # range [0,0.2] --> tau_i from the paper