Mercurial Hosting > traffic-intelligence
annotate c/feature-based-tracking.cpp @ 976:7f5cbdc107c5
corrected bug in converting time horizon to frames for internal computations (results for TTC, pPET and PET will be in frames)
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Mon, 05 Feb 2018 16:41:36 -0500 |
parents | 8ac7f61c6e4f |
children | 6c5ce3ec497e |
rev | line source |
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1 #include "Motion.hpp" |
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2 #include "Parameters.hpp" |
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3 #include "cvutils.hpp" |
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4 #include "utils.hpp" |
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5 |
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6 #include "src/Trajectory.h" |
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7 #include "src/TrajectoryDBAccessList.h" |
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8 #include "src/TrajectoryDBAccessBlob.h" |
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9 |
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10 #include "opencv2/core/core.hpp" |
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11 #include "opencv2/imgproc/imgproc.hpp" |
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12 #include "opencv2/video/tracking.hpp" |
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13 #include "opencv2/features2d/features2d.hpp" |
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14 #include "opencv2/highgui/highgui.hpp" |
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15 #include "opencv2/objdetect/objdetect.hpp" |
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16 #include "opencv2/calib3d/calib3d.hpp" |
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17 |
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18 #include <boost/foreach.hpp> |
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19 |
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20 #include <iostream> |
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21 #include <vector> |
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22 #include <ctime> |
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23 #include <cmath> |
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24 #include <memory> |
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25 #include <limits> |
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26 |
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27 using namespace std; |
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28 using namespace cv; |
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29 |
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30 void drawMatchesRelative(const vector<KeyPoint>& train, const vector<KeyPoint>& query, std::vector<cv::DMatch>& matches, Mat& img) { |
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31 for (int i = 0; i < (int)matches.size(); i++) |
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32 { |
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33 Point2f pt_new = query[matches[i].queryIdx].pt; |
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34 Point2f pt_old = train[matches[i].trainIdx].pt; |
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35 Point2f dist = pt_new - pt_old; |
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36 if (norm(dist) < 20) { |
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37 line(img, pt_new, pt_old, Scalar(125, 255, 125), 1); |
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38 circle(img, pt_old, 2, Scalar(255, 0, 125), 1); |
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39 } |
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40 } |
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41 } |
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42 |
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43 void drawOpticalFlow(const vector<Point2f>& prevPts, const vector<Point2f>& currPts, const vector<uchar> status, Mat& img) { |
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44 for (unsigned int i=0; i<status.size(); i++) { |
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45 if (status[i]) { |
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46 line(img, prevPts[i], currPts[i], Scalar(125, 255, 125), 1); |
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47 circle(img, prevPts[i], 2, Scalar(255, 0, 125), 1); |
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48 } |
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49 } |
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50 } |
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51 |
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52 struct FeaturePointMatch { |
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53 FeatureTrajectoryPtr feature; |
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54 int pointNum; |
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55 |
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56 FeaturePointMatch(FeatureTrajectoryPtr _feature, const int& _pointNum): |
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57 feature(_feature), pointNum(_pointNum) {} |
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58 }; |
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59 |
480 | 60 inline void saveFeatures(vector<FeatureTrajectoryPtr>& features, TrajectoryDBAccess<Point2f>& db, const string& positionsTableName, const string& velocitiesTableName) { |
61 BOOST_FOREACH(FeatureTrajectoryPtr f, features) f->write(db, positionsTableName, velocitiesTableName); | |
62 features.clear(); | |
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63 } |
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64 |
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65 void trackFeatures(const KLTFeatureTrackingParameters& params) { |
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66 Mat homography = ::loadMat(params.homographyFilename, " "); |
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67 Mat invHomography; |
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68 if (params.display && !homography.empty()) |
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69 invHomography = homography.inv(); |
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70 |
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71 float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement; |
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72 Size window = Size(params.windowSize, params.windowSize); |
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73 |
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74 int interpolationMethod = -1; |
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75 if (params.interpolationMethod == 0) |
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76 interpolationMethod = INTER_NEAREST; |
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77 else if (params.interpolationMethod == 1) |
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78 interpolationMethod = INTER_LINEAR; |
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79 else if (params.interpolationMethod == 2) |
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80 interpolationMethod = INTER_CUBIC; |
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81 else if (params.interpolationMethod == 3) |
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82 interpolationMethod = INTER_LANCZOS4; |
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83 else |
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84 cout << "Unsupported option " << interpolationMethod << " for interpolation method" << endl; |
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85 |
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86 // BruteForceMatcher<Hamming> descMatcher; |
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87 // vector<DMatch> matches; |
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88 |
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89 if(params.videoFilename.empty()) { |
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90 cout << "Empty video filename. Exiting." << endl; |
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91 exit(0); |
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92 } |
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93 |
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94 VideoCapture capture(params.videoFilename); |
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95 if(!capture.isOpened()) { |
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96 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl; |
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97 exit(0); |
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98 } |
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99 |
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100 Size videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT)); |
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101 unsigned int nFrames = capture.get(CV_CAP_PROP_FRAME_COUNT); |
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102 if (nFrames <= 0) { |
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103 cout << "Guessing that the number of frames could not be read: " << nFrames << endl; |
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104 nFrames = numeric_limits<int>::max(); |
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105 cout << "Setting arbitrarily high number for testing: " << nFrames << endl; |
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106 } |
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107 |
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108 cout << "Video " << params.videoFilename << |
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109 ": width=" << videoSize.width << |
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110 ", height=" << videoSize.height << |
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111 ", nframes=" << nFrames << endl; |
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112 |
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113 Mat map1, map2; |
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114 Mat intrinsicCameraMatrix, newIntrinsicCameraMatrix; |
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115 if (params.undistort) { |
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116 intrinsicCameraMatrix = ::loadMat(params.intrinsicCameraFilename, " "); |
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117 Size undistortedVideoSize = Size(static_cast<int>(round(videoSize.width*params.undistortedImageMultiplication)), static_cast<int>(round(videoSize.height*params.undistortedImageMultiplication))); |
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118 newIntrinsicCameraMatrix = getDefaultNewCameraMatrix(intrinsicCameraMatrix, undistortedVideoSize, true);// for some reason, it's double type //getOptimalNewCameraMatrix(intrinsicCameraMatrix, params.distortionCoefficients, videoSize, 1, undistortedVideoSize);//, 0, true); |
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119 initUndistortRectifyMap(intrinsicCameraMatrix, params.distortionCoefficients, Mat::eye(3,3, CV_32FC1) /* 0 ?*/, newIntrinsicCameraMatrix, undistortedVideoSize, CV_32FC1, map1, map2); |
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120 |
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121 cout << "Undistorted width=" << undistortedVideoSize.width << |
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122 ", height=" << undistortedVideoSize.height << endl; |
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123 } |
399
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124 |
146
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125 Mat mask = imread(params.maskFilename, 0); |
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126 if (mask.empty()) { |
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127 cout << "Mask filename " << params.maskFilename << " could not be opened." << endl; |
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128 mask = Mat::ones(videoSize, CV_8UC1); |
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129 } |
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130 |
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131 std::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
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132 trajectoryDB->connect(params.databaseFilename.c_str()); |
142
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133 trajectoryDB->createTable("positions"); |
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134 trajectoryDB->createTable("velocities"); |
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135 trajectoryDB->beginTransaction(); |
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136 |
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137 std::vector<Point2f> prevPts, currPts, newPts, undistortedPts; // all points but undistortedPts are in image space |
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138 std::vector<uchar> status; |
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139 std::vector<float> errors; |
127
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140 Mat prevDesc, currDesc; |
128
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141 |
230
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142 std::vector<FeatureTrajectoryPtr> lostFeatures; |
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143 std::vector<FeaturePointMatch> featurePointMatches; |
163
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144 |
133
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145 int key = '?'; |
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146 unsigned int savedFeatureId=0; |
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147 Mat frame, currentFrameBW, previousFrameBW, displayFrame; // = Mat::zeros(1, 1, CV_8UC1) |
227
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148 |
278
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149 unsigned int lastFrameNum = nFrames; |
228
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150 if (params.nFrames > 0) |
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151 lastFrameNum = MIN(params.frame1+static_cast<unsigned int>(params.nFrames), nFrames); |
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152 |
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153 capture.set(CV_CAP_PROP_POS_FRAMES, params.frame1); |
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154 for (unsigned int frameNum = params.frame1; (frameNum < lastFrameNum) && !::interruptionKey(key); frameNum++) { |
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155 capture >> frame; |
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156 if (frame.empty()) { |
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157 cout << "Empty frame " << frameNum << ", breaking (" << frame.empty() << " [" << frame.size().width << "x" << frame.size().height << "])" << endl; |
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158 break; |
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159 } else if (frameNum%50 ==0) |
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160 cout << "frame " << frameNum << endl; |
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161 |
655
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162 cvtColor(frame, currentFrameBW, CV_RGB2GRAY); |
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163 |
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164 if (!prevPts.empty()) { |
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165 currPts.clear(); |
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166 calcOpticalFlowPyrLK(previousFrameBW, currentFrameBW, prevPts, currPts, status, errors, window, params.pyramidLevel, TermCriteria(static_cast<int>(TermCriteria::COUNT)+static_cast<int>(TermCriteria::EPS) /* = 3 */, params.maxNumberTrackingIterations, params.minTrackingError), /* int flags = */ 0, params.minFeatureEigThreshold); |
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167 /// \todo try calcOpticalFlowFarneback |
128
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168 |
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169 if (params.undistort) |
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170 undistortPoints(currPts, undistortedPts, intrinsicCameraMatrix, params.distortionCoefficients); |
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171 else |
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172 undistortedPts =currPts; |
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173 |
655
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174 std::vector<Point2f> trackedPts; |
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175 std::vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); |
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176 while (iter != featurePointMatches.end()) { |
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177 bool deleteFeature = false; |
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178 |
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179 int currPtX = static_cast<int>(floor(currPts[iter->pointNum].x)); |
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180 int currPtY = static_cast<int>(floor(currPts[iter->pointNum].y)); |
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181 if ((status[iter->pointNum] =! 0) && |
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182 (currPtX >= 0) && (currPtX < videoSize.width) && |
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183 (currPtY >= 0) && (currPtY < videoSize.height) && |
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184 (mask.at<uchar>(currPtY, currPtX) != 0)) { |
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185 iter->feature->addPoint(frameNum, undistortedPts[iter->pointNum], homography); |
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186 |
655
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187 deleteFeature = iter->feature->isDisplacementSmall(params.nDisplacements, minTotalFeatureDisplacement) |
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188 || !iter->feature->isMotionSmooth(params.accelerationBound, params.deviationBound); |
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189 if (deleteFeature) |
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190 iter->feature->shorten(); |
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191 } else |
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192 deleteFeature = true; |
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193 |
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194 if (deleteFeature) { |
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195 if (iter->feature->length() >= params.minFeatureTime) { |
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196 iter->feature->setId(savedFeatureId); |
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197 savedFeatureId++; |
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198 iter->feature->movingAverage(params.nFramesSmoothing); |
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199 lostFeatures.push_back(iter->feature); |
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200 } |
655
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201 iter = featurePointMatches.erase(iter); |
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202 } else { |
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203 trackedPts.push_back(currPts[iter->pointNum]); |
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204 iter->pointNum = trackedPts.size()-1; |
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205 iter++; |
139
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206 } |
125
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207 } |
655
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208 currPts = trackedPts; |
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209 assert(currPts.size() == featurePointMatches.size()); |
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210 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities"); |
933
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211 |
655
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212 if (params.display) { |
924
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213 if (params.undistort) |
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214 remap(frame, displayFrame, map1, map2, interpolationMethod, BORDER_CONSTANT, 0.); |
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215 else |
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216 displayFrame = frame.clone(); |
655
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217 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches) |
933
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218 fp.feature->draw(displayFrame, invHomography, newIntrinsicCameraMatrix, Colors::red()); |
655
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219 } |
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220 } |
800
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modified so there is no tracking outside of the mask (does not continue if features can still be matched) as requested
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221 |
655
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222 // adding new features, using mask around existing feature positions |
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223 Mat featureMask = mask.clone(); |
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224 for (unsigned int n=0;n<currPts.size(); n++) |
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225 for (int j=MAX(0, currPts[n].x-params.minFeatureDistanceKLT); j<MIN(videoSize.width, currPts[n].x+params.minFeatureDistanceKLT+1); j++) |
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226 for (int i=MAX(0, currPts[n].y-params.minFeatureDistanceKLT); i<MIN(videoSize.height, currPts[n].y+params.minFeatureDistanceKLT+1); i++) |
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227 featureMask.at<uchar>(i,j)=0; |
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228 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.blockSize, params.useHarrisDetector, params.k); |
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229 if (params.undistort) |
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230 undistortPoints(newPts, undistortedPts, intrinsicCameraMatrix, params.distortionCoefficients); |
926
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231 else |
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232 undistortedPts = newPts; |
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233 |
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234 for (unsigned int i=0; i<newPts.size(); i++) { |
926
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235 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, undistortedPts[i], homography)); |
655
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236 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size())); |
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237 currPts.push_back(newPts[i]); |
655
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238 } |
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239 |
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240 if (params.display && !displayFrame.empty()) { |
655
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241 imshow("mask", featureMask*256); |
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242 imshow("frame", displayFrame); |
655
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243 key = waitKey(2); |
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244 } |
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245 previousFrameBW = currentFrameBW.clone(); |
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246 prevPts = currPts; |
480 | 247 } |
248 | |
249 // save the remaining currently tracked features | |
250 std::vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); | |
251 while (iter != featurePointMatches.end()) { | |
252 if (iter->feature->length() >= params.minFeatureTime) { | |
253 iter->feature->setId(savedFeatureId); | |
254 savedFeatureId++; | |
481
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480
diff
changeset
|
255 iter->feature->movingAverage(params.nFramesSmoothing); |
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480
diff
changeset
|
256 iter->feature->write(*trajectoryDB, "positions", "velocities"); |
480 | 257 } |
258 iter++; | |
259 } | |
121
c4d4b5b93add
copied the video_homography opencv sample
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
119
diff
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|
260 |
142
a3532db00c28
added code to write velocities
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141
diff
changeset
|
261 trajectoryDB->endTransaction(); |
136
0f790de9437e
renamed Feature to Motion files and added code to test blob db
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135
diff
changeset
|
262 trajectoryDB->disconnect(); |
164
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parents:
163
diff
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|
263 } |
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163
diff
changeset
|
264 |
169
5f705809d37a
created groupFeatures function
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168
diff
changeset
|
265 void groupFeatures(const KLTFeatureTrackingParameters& params) { |
654
045d05cef9d0
updating to c++11 capabilities
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542
diff
changeset
|
266 std::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
169
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168
diff
changeset
|
267 bool success = trajectoryDB->connect(params.databaseFilename.c_str()); |
202
b0b964ba9489
added early saving of objects
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parents:
194
diff
changeset
|
268 trajectoryDB->createObjectTable("objects", "objects_features"); |
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194
diff
changeset
|
269 unsigned int savedObjectId=0; |
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diff
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|
270 |
225
d4d3b1e8a9f1
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222
diff
changeset
|
271 trajectoryDB->createInstants("table"); |
710
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679
diff
changeset
|
272 //trajectoryDB->createIndex("positions","trajectory_id"); // does not seem to make loading features faster |
70a3cdf0dbb3
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679
diff
changeset
|
273 //trajectoryDB->createIndex("velocities","trajectory_id"); |
221
bc93e87a2108
cleaned and corrected connected components and feature groups
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219
diff
changeset
|
274 |
225
d4d3b1e8a9f1
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222
diff
changeset
|
275 unsigned int maxTrajectoryLength = 0; |
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diff
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|
276 success = trajectoryDB->maxTrajectoryLength(maxTrajectoryLength); |
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diff
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|
277 if (!success || maxTrajectoryLength == 0) { |
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diff
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278 cout << "problem with trajectory length " << success << endl; |
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diff
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279 exit(0); |
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diff
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|
280 } |
222
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221
diff
changeset
|
281 cout << "Longest trajectory: " << maxTrajectoryLength << endl; |
219
841a1714f702
added comments for future development
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207
diff
changeset
|
282 |
191
0e60a306d324
added basic code to identify features and save them (crash)
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parents:
189
diff
changeset
|
283 FeatureGraph featureGraph(params.mmConnectionDistance, params.mmSegmentationDistance, params.minFeatureTime, params.minNFeaturesPerGroup); |
180
3a4eef37384f
method to add features and vertices to graph
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179
diff
changeset
|
284 |
169
5f705809d37a
created groupFeatures function
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168
diff
changeset
|
285 // main loop |
227
b7612c6d5702
cleaned the code
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225
diff
changeset
|
286 unsigned int frameNum; |
b7612c6d5702
cleaned the code
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225
diff
changeset
|
287 unsigned int firstFrameNum = -1, lastFrameNum = -1; |
225
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222
diff
changeset
|
288 trajectoryDB->firstLastInstants(firstFrameNum, lastFrameNum); |
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added code to process only needed frames based on saved features
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222
diff
changeset
|
289 firstFrameNum = MAX(firstFrameNum, params.frame1); |
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222
diff
changeset
|
290 if (params.nFrames>0) |
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diff
changeset
|
291 lastFrameNum = MIN(lastFrameNum,params.frame1+params.nFrames); |
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added code to process only needed frames based on saved features
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222
diff
changeset
|
292 for (frameNum = firstFrameNum; frameNum<lastFrameNum; frameNum ++) { |
174
ec9734015d53
tested loading trajectory by id numbers
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172
diff
changeset
|
293 vector<int> trajectoryIds; |
231
249d65ff6c35
merged modifications for windows
Nicolas Saunier <nicolas.saunier@polymtl.ca>
diff
changeset
|
294 success = trajectoryDB->trajectoryIdEndingAt(trajectoryIds, frameNum); |
225
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added code to process only needed frames based on saved features
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222
diff
changeset
|
295 if (frameNum%100 ==0) |
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222
diff
changeset
|
296 cout << "frame " << frameNum << endl; |
222
426321b46e44
temporary trajectory instants table
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221
diff
changeset
|
297 #if DEBUG |
174
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tested loading trajectory by id numbers
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172
diff
changeset
|
298 cout << trajectoryIds.size() << " trajectories " << endl; |
222
426321b46e44
temporary trajectory instants table
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221
diff
changeset
|
299 #endif |
174
ec9734015d53
tested loading trajectory by id numbers
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172
diff
changeset
|
300 BOOST_FOREACH(int trajectoryId, trajectoryIds) { |
177
ae2286b1a3fd
added loading FeatureTrajectory from database, printing
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parents:
176
diff
changeset
|
301 FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(trajectoryId, *trajectoryDB, "positions", "velocities")); |
180
3a4eef37384f
method to add features and vertices to graph
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179
diff
changeset
|
302 featureGraph.addFeature(ft); |
174
ec9734015d53
tested loading trajectory by id numbers
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172
diff
changeset
|
303 } |
172
e508bb0cbb64
modified comments
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parents:
169
diff
changeset
|
304 |
222
426321b46e44
temporary trajectory instants table
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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221
diff
changeset
|
305 // check for connected components |
225
d4d3b1e8a9f1
added code to process only needed frames based on saved features
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222
diff
changeset
|
306 int lastInstant = frameNum+params.minFeatureTime-maxTrajectoryLength; |
231
249d65ff6c35
merged modifications for windows
Nicolas Saunier <nicolas.saunier@polymtl.ca>
diff
changeset
|
307 if (lastInstant > 0 && frameNum%10==0) { |
225
d4d3b1e8a9f1
added code to process only needed frames based on saved features
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
222
diff
changeset
|
308 featureGraph.connectedComponents(lastInstant); |
391
03dbecd3a887
modified feature grouping to return vectors of pointers to feature trajectories
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
363
diff
changeset
|
309 vector<vector<FeatureTrajectoryPtr> > featureGroups; |
03dbecd3a887
modified feature grouping to return vectors of pointers to feature trajectories
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363
diff
changeset
|
310 featureGraph.getFeatureGroups(featureGroups); |
225
d4d3b1e8a9f1
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parents:
222
diff
changeset
|
311 for (unsigned int i=0; i<featureGroups.size(); ++i) { |
391
03dbecd3a887
modified feature grouping to return vectors of pointers to feature trajectories
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parents:
363
diff
changeset
|
312 vector<unsigned int> featureNumbers; |
03dbecd3a887
modified feature grouping to return vectors of pointers to feature trajectories
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parents:
363
diff
changeset
|
313 for (unsigned int j=0; j<featureGroups[i].size(); ++j) |
03dbecd3a887
modified feature grouping to return vectors of pointers to feature trajectories
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363
diff
changeset
|
314 featureNumbers.push_back(featureGroups[i][j]->getId()); |
716
85af65b6d531
corrected major bug slowing feature grouping
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
710
diff
changeset
|
315 trajectoryDB->writeObject(savedObjectId, featureNumbers, 0 /* unknown type */, 1, string("objects"), string("objects_features")); |
225
d4d3b1e8a9f1
added code to process only needed frames based on saved features
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222
diff
changeset
|
316 savedObjectId++; |
d4d3b1e8a9f1
added code to process only needed frames based on saved features
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parents:
222
diff
changeset
|
317 } |
188
1435965d8181
work on connected components
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
186
diff
changeset
|
318 } |
222
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319 |
225
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320 if (frameNum%100 ==0) |
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321 cout << featureGraph.informationString() << endl; |
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322 } |
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323 |
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324 // save remaining objects |
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325 featureGraph.connectedComponents(frameNum+maxTrajectoryLength+1); |
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326 vector<vector<FeatureTrajectoryPtr> > featureGroups; |
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327 featureGraph.getFeatureGroups(featureGroups); |
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328 for (unsigned int i=0; i<featureGroups.size(); ++i) { |
391
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329 vector<unsigned int> featureNumbers; |
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330 for (unsigned int j=0; j<featureGroups[i].size(); ++j) |
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331 featureNumbers.push_back(featureGroups[i][j]->getId()); |
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332 trajectoryDB->writeObject(savedObjectId, featureNumbers, 0 /* unknown */, 1, string("objects"), string("objects_features")); |
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333 savedObjectId++; |
180
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334 } |
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335 |
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336 trajectoryDB->endTransaction(); |
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337 trajectoryDB->disconnect(); |
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338 } |
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339 |
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340 void loadingTimes(const KLTFeatureTrackingParameters& params) { |
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341 std::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
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342 bool success = trajectoryDB->connect(params.databaseFilename.c_str()); |
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343 |
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344 vector<std::shared_ptr<Trajectory<Point2f> > > trajectories; |
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345 //cout << trajectories.size() << endl; |
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346 std::clock_t c_start = std::clock(); |
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347 success = trajectoryDB->read(trajectories, "positions"); |
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348 std::clock_t c_end = std::clock(); |
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349 if (!success) |
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350 cout << "Issue with db reading" << endl; |
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351 cout << "Loaded " << trajectories.size() << " trajectories in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl; |
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352 |
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353 std::shared_ptr<Trajectory<cv::Point2f> > trajectory; |
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354 c_start = std::clock(); |
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355 for (unsigned int i = 0; i<trajectories.size(); ++i) { |
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356 success = trajectoryDB->read(trajectory, i, "positions"); |
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357 } |
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358 c_end = std::clock(); |
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359 cout << "Loaded " << trajectories.size() << " trajectories one by one in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl; |
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360 |
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361 trajectoryDB->endTransaction(); |
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362 trajectoryDB->disconnect(); |
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363 } |
169
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364 |
164
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365 int main(int argc, char *argv[]) { |
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366 KLTFeatureTrackingParameters params(argc, argv); |
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367 cout << params.parameterDescription << endl; |
654
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368 |
234
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369 if (params.trackFeatures) { |
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370 cout << "The program tracks features" << endl; |
164
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371 trackFeatures(params); |
234
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372 } else if (params.groupFeatures) { |
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373 cout << "The program groups features" << endl; |
169
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374 groupFeatures(params); |
654
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375 } else if (params.loadingTime) { |
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376 cout << "The program reports loading times" << endl; |
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377 loadingTimes(params); |
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378 } else { |
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379 cout << "Main option missing or misspelt" << endl; |
234
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380 } |
164
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381 |
117
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382 return 0; |
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383 } |
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384 |
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385 /* ------------------ DOCUMENTATION ------------------ */ |
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386 |
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387 |
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388 /*! \mainpage |
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389 |
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390 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are: |
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391 |
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392 - \ref feature_based_tracking |
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393 |
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394 The code is partially self-described using the doxygen tool and comment formatting. The documentation can be extracted using doxygen, typing \c doxygen in the main directory (or <tt>make doc</tt> on a system with the Makefile tool installed). |
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395 |
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396 */ |
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397 |
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398 /*! \page feature_based_tracking Feature-based Tracking: User Manual |
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399 |
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400 This document describes a software tool for object tracking in video data, developed for road traffic monitoring and safety diagnosis. It is part of a larger collection of software tools for transportation called Traffic Intelligence. |
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401 |
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402 The tool relies on feature-based tracking, a robust object tracking methods, particularly suited for the extraction of traffic data such as trajectories and speeds. The best description of this method is given in <a href="http://nicolas.saunier.confins.net/data/saunier06crv.html">this paper</a>. The program has a command line interface and this document will shortly explain how to use the tool. Keep in mind this is a work in progress and major changes are continuously being made. |
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403 |
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404 \section License |
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405 |
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406 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license). |
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407 |
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408 If you make use of this piece of software, please cite one of my paper, e.g. N. Saunier, T. Sayed and K. Ismail. Large Scale Automated Analysis of Vehicle Interactions and Collisions. Transportation Research Record: Journal of the Transportation Research Board, 2147:42-50, 2010. I would be very happy in any case to know about any use of the code, and to discuss any opportunity for collaboration. |
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409 |
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410 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net. |
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411 |
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412 */ |