Mercurial Hosting > traffic-intelligence
annotate c/feature-based-tracking.cpp @ 804:17e54690af8a dev
work in progress, not fully functional yet
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Wed, 01 Jun 2016 17:57:49 -0400 |
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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.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 refHomography = ::loadMat(params.homographyFilename, " "); |
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67 //if (params.stabilize && refHomography.empty()) |
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68 // refHomography = Mat::eye(3, 3, CV_64FC1); |
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69 //Mat stabilizationHomography(3,3,CV_64FC1), homography(3,3,CV_64FC1); |
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70 Mat stabilizationHomography, homography; |
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71 if (!params.stabilize) |
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72 homography = refHomography; |
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73 |
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74 float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement; |
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75 Size window = Size(params.windowSize, params.windowSize); |
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76 |
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77 int interpolationMethod = -1; |
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78 if (params.interpolationMethod == 0) |
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79 interpolationMethod = INTER_NEAREST; |
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80 else if (params.interpolationMethod == 1) |
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81 interpolationMethod = INTER_LINEAR; |
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82 else if (params.interpolationMethod == 2) |
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83 interpolationMethod = INTER_CUBIC; |
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84 else if (params.interpolationMethod == 3) |
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85 interpolationMethod = INTER_LANCZOS4; |
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86 else |
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87 cout << "Unsupported option " << interpolationMethod << " for interpolation method" << endl; |
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88 |
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89 // BruteForceMatcher<Hamming> descMatcher; |
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90 // vector<DMatch> matches; |
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91 |
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92 if(params.videoFilename.empty()) { |
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93 cout << "Empty video filename. Exiting." << endl; |
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94 exit(0); |
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95 } |
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96 |
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97 VideoCapture capture(params.videoFilename); |
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98 if(!capture.isOpened()) { |
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99 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl; |
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100 exit(0); |
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101 } |
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102 |
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103 Size videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT)); |
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104 unsigned int nFrames = capture.get(CV_CAP_PROP_FRAME_COUNT); |
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105 if (nFrames <= 0) { |
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106 cout << "Guessing that the number of frames could not be read: " << nFrames << endl; |
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107 nFrames = numeric_limits<int>::max(); |
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108 cout << "Setting arbitrarily high number for testing: " << nFrames << endl; |
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109 } |
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110 |
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111 cout << "Video " << params.videoFilename << |
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112 ": width=" << videoSize.width << |
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113 ", height=" << videoSize.height << |
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114 ", nframes=" << nFrames << endl; |
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115 |
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116 Mat map1, map2; |
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117 if (params.undistort) { |
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118 Mat intrinsicCameraMatrix = ::loadMat(params.intrinsicCameraFilename, " "); |
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119 Mat newIntrinsicCameraMatrix = intrinsicCameraMatrix.clone(); |
509
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120 videoSize = Size(static_cast<int>(round(videoSize.width*params.undistortedImageMultiplication)), static_cast<int>(round(videoSize.height*params.undistortedImageMultiplication))); |
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121 newIntrinsicCameraMatrix.at<float>(0,2) = videoSize.width/2.; |
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122 newIntrinsicCameraMatrix.at<float>(1,2) = videoSize.height/2.; |
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123 initUndistortRectifyMap(intrinsicCameraMatrix, params.distortionCoefficients, Mat::eye(3, 3, CV_32FC1), newIntrinsicCameraMatrix, videoSize, CV_32FC1, map1, map2); |
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124 |
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125 cout << "Undistorted width=" << videoSize.width << |
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126 ", height=" << videoSize.height << endl; |
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127 } |
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128 |
146
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129 Mat mask = imread(params.maskFilename, 0); |
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130 if (mask.empty()) { |
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131 cout << "Mask filename " << params.maskFilename << " could not be opened." << endl; |
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132 mask = Mat::ones(videoSize, CV_8UC1); |
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133 } |
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134 Mat featureMask = mask.clone(); |
146
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135 |
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136 std::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
136
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137 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>(); |
138
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138 trajectoryDB->connect(params.databaseFilename.c_str()); |
142
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139 trajectoryDB->createTable("positions"); |
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140 trajectoryDB->createTable("velocities"); |
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141 trajectoryDB->beginTransaction(); |
133
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142 |
230
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143 std::vector<KeyPoint> prevKpts, currKpts; |
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144 std::vector<Point2f> prevPts, currPts, newPts, stabilizationRefPts, stabilizationCurrPts; |
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145 std::vector<uchar> status, stabilizationPtsStatus; |
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146 std::vector<float> errorPts, stabilizationErrorPts; |
127
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147 Mat prevDesc, currDesc; |
128
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148 |
230
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149 std::vector<FeatureTrajectoryPtr> lostFeatures; |
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150 std::vector<FeaturePointMatch> featurePointMatches; |
163
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diff
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151 |
133
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152 int key = '?'; |
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153 unsigned int savedFeatureId=0; |
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154 Mat frame = Mat::zeros(1, 1, CV_8UC1), currentFrameBW, previousFrameBW, undistortedFrame, homographyFrameBW, homographyFrame; |
802
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155 |
803
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156 if (params.stabilize) { |
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157 homographyFrame = imread(params.frameHomographyFilename); |
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158 if (homographyFrame.empty()) |
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159 cout << "Homography frame filename " << params.frameHomographyFilename << " could not be opened." << endl; |
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160 else { |
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161 if (params.undistort) { |
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162 remap(homographyFrame, undistortedFrame, map1, map2, interpolationMethod, BORDER_CONSTANT, 0.); |
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163 homographyFrame = undistortedFrame; |
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164 } |
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165 |
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166 cvtColor(homographyFrame, homographyFrameBW, CV_RGB2GRAY); |
804
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167 goodFeaturesToTrack(homographyFrameBW, stabilizationRefPts, params.maxNFeatures, MAX(0.01, params.featureQuality), params.minFeatureDistanceKLT, mask, params.blockSize, params.useHarrisDetector, params.k); // take higher quality features? |
803
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168 } |
802
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169 } |
d3e8dd9f3ca4
current dev for drone stabilization
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diff
changeset
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170 |
278
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resolved issue 2 and problem with negative nframes parameter
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234
diff
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|
171 unsigned int lastFrameNum = nFrames; |
228
23da16442433
minor modifications for unsigned int (nframes is now 0 to process all frames)
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172 if (params.nFrames > 0) |
278
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resolved issue 2 and problem with negative nframes parameter
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173 lastFrameNum = MIN(params.frame1+static_cast<unsigned int>(params.nFrames), nFrames); |
495
82c06ad62254
added parameter description with ranges
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diff
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174 |
804
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175 // Main Loop |
655
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176 capture.set(CV_CAP_PROP_POS_FRAMES, params.frame1); |
227
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cleaned the code
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diff
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177 for (unsigned int frameNum = params.frame1; (frameNum < lastFrameNum) && !::interruptionKey(key); frameNum++) { |
655
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178 capture >> frame; |
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179 if (frame.empty()) { |
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180 cout << "Empty frame " << frameNum << ", breaking (" << frame.empty() << " [" << frame.size().width << "x" << frame.size().height << "])" << endl; |
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181 break; |
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182 } else if (frameNum%50 ==0) |
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183 cout << "frame " << frameNum << endl; |
532
018653d1db3c
corrected bug with empty frames (the program will stop cleanly and store features
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diff
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184 |
802
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185 cvtColor(frame, currentFrameBW, CV_RGB2GRAY); |
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current dev for drone stabilization
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186 |
655
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removed the abstract class to represent folders of images or video files since the capability is now built in OpenCV
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187 if (params.undistort) { |
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188 remap(currentFrameBW, undistortedFrame, map1, map2, interpolationMethod, BORDER_CONSTANT, 0.); |
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189 currentFrameBW = undistortedFrame; |
655
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190 if (frame.size() != videoSize) { |
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191 cout << "Different frame size " << frameNum << ", breaking ([" << frame.size().width << "x" << frame.size().height << "])" << endl; |
534
d0419b1267dd
fixing size issue when testing frames in main loop
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parents:
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|
192 break; |
507
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first version with undistort implemented in the feature tracking process
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193 } |
655
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194 } |
800
2cade72d75ad
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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195 |
655
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196 if (!prevPts.empty()) { |
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197 currPts.clear(); |
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198 calcOpticalFlowPyrLK(previousFrameBW, currentFrameBW, prevPts, currPts, status, errorPts, window, params.pyramidLevel, TermCriteria(static_cast<int>(TermCriteria::COUNT)+static_cast<int>(TermCriteria::EPS) /* = 3 */, params.maxNumberTrackingIterations, params.minTrackingError), /* int flags = */ 0, params.minFeatureEigThreshold); |
655
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removed the abstract class to represent folders of images or video files since the capability is now built in OpenCV
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199 /// \todo try calcOpticalFlowFarneback |
128
536510f60854
new features generated as needed
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diff
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200 |
803
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201 if (params.stabilize) { |
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202 calcOpticalFlowPyrLK(homographyFrameBW, currentFrameBW, stabilizationRefPts, stabilizationCurrPts, stabilizationPtsStatus, stabilizationErrorPts, window, params.pyramidLevel, TermCriteria(static_cast<int>(TermCriteria::COUNT)+static_cast<int>(TermCriteria::EPS) /* = 3 */, params.maxNumberTrackingIterations, params.minTrackingError), /* int flags = */ 0, params.minFeatureEigThreshold); |
802
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203 |
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204 std::vector<Point2f> stabilizationRefPts2, stabilizationCurrPts2; |
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205 for (unsigned int i=0; i<stabilizationRefPts.size(); i++) |
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206 if (stabilizationPtsStatus[i]) { |
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207 stabilizationRefPts2.push_back(stabilizationRefPts[i]); |
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208 stabilizationCurrPts2.push_back(stabilizationCurrPts[i]); |
803
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209 } |
804
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210 stabilizationHomography = findHomography(stabilizationCurrPts2, stabilizationRefPts2, CV_RANSAC, params.stabilizeRansacReprojThreshold); |
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211 //cout << stabilizationHomography << endl; |
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212 //cout << stabilizationHomography.type() << " " << refHomography.type() << endl; |
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213 //for (unsigned int i=0; i<MIN(stabilizationRefPts.size(), 10); i++) { |
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214 //cout << stabilizationCurrPts2[i] << " " << stabilizationRefPts2[i] << ": projected " << ::project<double>(stabilizationCurrPts2[i], stabilizationHomography) << endl; |
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215 //cout << stabilizationHomography.at<double>(0,0)*stabilizationCurrPts2[i].x+stabilizationHomography.at<double>(0,1)*stabilizationCurrPts2[i].y+stabilizationHomography.at<double>(0,2) << " " << stabilizationHomography.at<double>(1,0)*stabilizationCurrPts2[i].x+stabilizationHomography.at<double>(1,1)*stabilizationCurrPts2[i].y+stabilizationHomography.at<double>(1,2) << " " << stabilizationHomography.at<double>(2,0)*stabilizationCurrPts2[i].x+stabilizationHomography.at<double>(2,1)*stabilizationCurrPts2[i].y+stabilizationHomography.at<double>(2,2) << endl; |
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216 //} |
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217 if (stabilizationHomography.empty()) { |
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218 homography = refHomography; |
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219 featureMask = mask.clone(); |
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220 } else { |
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221 if (refHomography.empty()) |
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222 homography = stabilizationHomography; |
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223 else |
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224 homography = refHomography*stabilizationHomography; |
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225 //cout << refHomography << " * " << stabilizationHomography << " = " << homography << endl; |
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226 warpPerspective(mask, featureMask, stabilizationHomography, videoSize, INTER_LINEAR+WARP_INVERSE_MAP, BORDER_CONSTANT, 0); |
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227 } |
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228 } else |
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229 featureMask = mask.clone(); |
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230 |
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231 |
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232 std::vector<Point2f> trackedPts; |
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233 std::vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); |
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234 while (iter != featurePointMatches.end()) { |
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235 bool deleteFeature = false; |
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236 |
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237 if (status[iter->pointNum]) { |
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238 Point2f homographyFramePt = ::project<double>(currPts[iter->pointNum], stabilizationHomography); // project to space of homography frame (if not stabilization, stabilizationHomography should be empty) |
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239 cout << currPts[iter->pointNum] << ", " << homographyFramePt << endl; |
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240 if (::inImage(homographyFramePt, videoSize) && (mask.at<uchar>(static_cast<int>(round(homographyFramePt.y)), static_cast<int>(round(homographyFramePt.x))) != 0)) { // check point is in mask |
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241 iter->feature->addPoint(frameNum, ::project<double>(homographyFramePt, refHomography)); |
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242 //cout << *(iter->feature) << endl; |
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243 deleteFeature = iter->feature->isDisplacementSmall(params.nDisplacements, minTotalFeatureDisplacement) |
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244 || !iter->feature->isMotionSmooth(params.accelerationBound, params.deviationBound); |
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245 if (deleteFeature) |
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246 iter->feature->shorten(); |
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247 } else |
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248 deleteFeature = true; |
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249 } else |
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250 deleteFeature = true; |
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251 |
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252 if (deleteFeature) { |
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253 if (iter->feature->length() >= params.minFeatureTime) { |
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254 iter->feature->setId(savedFeatureId); |
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255 savedFeatureId++; |
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256 iter->feature->movingAverage(params.nFramesSmoothing); |
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257 lostFeatures.push_back(iter->feature); |
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258 } |
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259 iter = featurePointMatches.erase(iter); |
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260 } else { |
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261 trackedPts.push_back(currPts[iter->pointNum]); |
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262 iter->pointNum = trackedPts.size()-1; |
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263 iter++; |
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264 } |
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265 } |
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266 currPts = trackedPts; |
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267 assert(currPts.size() == featurePointMatches.size()); |
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268 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities"); |
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269 |
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270 if (params.display) { |
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271 cout << featurePointMatches.size() << " matches" << endl; |
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272 Mat invHomography; |
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273 if (!homography.empty()) |
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274 invHomography = homography.inv(); |
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275 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches) |
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276 fp.feature->draw(frame, invHomography, Colors::red()); |
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277 } |
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278 } |
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279 |
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280 // adding new features, using mask around existing feature positions |
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281 for (unsigned int n=0;n<currPts.size(); n++) |
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282 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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283 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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284 featureMask.at<uchar>(i,j)=0; |
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285 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.blockSize, params.useHarrisDetector, params.k); |
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286 BOOST_FOREACH(Point2f p, newPts) { |
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287 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, ::project<double>(::project<double>(p, stabilizationHomography), refHomography))); |
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288 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size())); |
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289 currPts.push_back(p); |
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290 } |
128
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291 |
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292 if (params.display) { |
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293 cout << currPts.size() << " current points" << endl; |
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294 Mat maskedFrame; |
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295 cvtColor(featureMask*256, maskedFrame, CV_GRAY2RGB); |
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296 addWeighted(frame, 0.5, maskedFrame, 0.5, 0.0, maskedFrame); |
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297 imshow("masked frame", maskedFrame); |
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298 //imshow("mask", featureMask*256); |
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299 imshow("frame", frame); |
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300 if (params.stabilize && !stabilizationHomography.empty()) { |
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301 Mat warped, vis; |
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302 warpPerspective(frame, warped, stabilizationHomography, videoSize); |
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303 addWeighted(homographyFrame, 0.5, warped, 0.5, 0.0, vis); |
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304 imshow("warped frame", vis); |
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305 } |
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306 key = waitKey(0); |
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307 } |
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308 previousFrameBW = currentFrameBW.clone(); |
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309 prevPts = currPts; |
480 | 310 } |
311 | |
312 // save the remaining currently tracked features | |
313 std::vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); | |
314 while (iter != featurePointMatches.end()) { | |
315 if (iter->feature->length() >= params.minFeatureTime) { | |
316 iter->feature->setId(savedFeatureId); | |
317 savedFeatureId++; | |
481
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318 iter->feature->movingAverage(params.nFramesSmoothing); |
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319 iter->feature->write(*trajectoryDB, "positions", "velocities"); |
480 | 320 } |
321 iter++; | |
322 } | |
121
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323 |
142
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324 trajectoryDB->endTransaction(); |
136
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325 trajectoryDB->disconnect(); |
164
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326 } |
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327 |
169
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328 void groupFeatures(const KLTFeatureTrackingParameters& params) { |
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329 std::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
169
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330 bool success = trajectoryDB->connect(params.databaseFilename.c_str()); |
202
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331 trajectoryDB->createObjectTable("objects", "objects_features"); |
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332 unsigned int savedObjectId=0; |
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333 |
225
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334 trajectoryDB->createInstants("table"); |
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335 //trajectoryDB->createIndex("positions","trajectory_id"); // does not seem to make loading features faster |
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336 //trajectoryDB->createIndex("velocities","trajectory_id"); |
221
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337 |
225
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338 unsigned int maxTrajectoryLength = 0; |
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339 success = trajectoryDB->maxTrajectoryLength(maxTrajectoryLength); |
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340 if (!success || maxTrajectoryLength == 0) { |
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341 cout << "problem with trajectory length " << success << endl; |
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342 exit(0); |
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343 } |
222
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344 cout << "Longest trajectory: " << maxTrajectoryLength << endl; |
219
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345 |
191
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346 FeatureGraph featureGraph(params.mmConnectionDistance, params.mmSegmentationDistance, params.minFeatureTime, params.minNFeaturesPerGroup); |
180
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347 |
169
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348 // main loop |
227
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349 unsigned int frameNum; |
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350 unsigned int firstFrameNum = -1, lastFrameNum = -1; |
225
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351 trajectoryDB->firstLastInstants(firstFrameNum, lastFrameNum); |
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352 firstFrameNum = MAX(firstFrameNum, params.frame1); |
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353 if (params.nFrames>0) |
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354 lastFrameNum = MIN(lastFrameNum,params.frame1+params.nFrames); |
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355 for (frameNum = firstFrameNum; frameNum<lastFrameNum; frameNum ++) { |
174
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356 vector<int> trajectoryIds; |
231
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357 success = trajectoryDB->trajectoryIdEndingAt(trajectoryIds, frameNum); |
225
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358 if (frameNum%100 ==0) |
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359 cout << "frame " << frameNum << endl; |
222
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360 #if DEBUG |
174
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361 cout << trajectoryIds.size() << " trajectories " << endl; |
222
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362 #endif |
174
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363 BOOST_FOREACH(int trajectoryId, trajectoryIds) { |
177
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364 FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(trajectoryId, *trajectoryDB, "positions", "velocities")); |
180
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365 featureGraph.addFeature(ft); |
174
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366 } |
172
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367 |
222
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368 // check for connected components |
225
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369 int lastInstant = frameNum+params.minFeatureTime-maxTrajectoryLength; |
231
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370 if (lastInstant > 0 && frameNum%10==0) { |
225
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371 featureGraph.connectedComponents(lastInstant); |
391
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372 vector<vector<FeatureTrajectoryPtr> > featureGroups; |
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373 featureGraph.getFeatureGroups(featureGroups); |
225
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374 for (unsigned int i=0; i<featureGroups.size(); ++i) { |
391
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375 vector<unsigned int> featureNumbers; |
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376 for (unsigned int j=0; j<featureGroups[i].size(); ++j) |
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377 featureNumbers.push_back(featureGroups[i][j]->getId()); |
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378 trajectoryDB->writeObject(savedObjectId, featureNumbers, 0 /* unknown type */, 1, string("objects"), string("objects_features")); |
225
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379 savedObjectId++; |
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380 } |
188
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381 } |
222
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382 |
225
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383 if (frameNum%100 ==0) |
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384 cout << featureGraph.informationString() << endl; |
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385 } |
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386 |
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387 // save remaining objects |
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388 featureGraph.connectedComponents(frameNum+maxTrajectoryLength+1); |
391
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389 vector<vector<FeatureTrajectoryPtr> > featureGroups; |
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390 featureGraph.getFeatureGroups(featureGroups); |
225
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391 for (unsigned int i=0; i<featureGroups.size(); ++i) { |
391
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392 vector<unsigned int> featureNumbers; |
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393 for (unsigned int j=0; j<featureGroups[i].size(); ++j) |
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394 featureNumbers.push_back(featureGroups[i][j]->getId()); |
412
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corrected grouping bug (last object type -1) and added script to rescale homographies
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395 trajectoryDB->writeObject(savedObjectId, featureNumbers, 0 /* unknown */, 1, string("objects"), string("objects_features")); |
225
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396 savedObjectId++; |
180
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397 } |
169
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398 |
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399 trajectoryDB->endTransaction(); |
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400 trajectoryDB->disconnect(); |
654
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401 } |
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402 |
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403 void loadingTimes(const KLTFeatureTrackingParameters& params) { |
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404 std::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
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405 bool success = trajectoryDB->connect(params.databaseFilename.c_str()); |
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406 |
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407 vector<std::shared_ptr<Trajectory<Point2f> > > trajectories; |
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408 //cout << trajectories.size() << endl; |
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409 std::clock_t c_start = std::clock(); |
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410 success = trajectoryDB->read(trajectories, "positions"); |
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411 std::clock_t c_end = std::clock(); |
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412 if (!success) |
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413 cout << "Issue with db reading" << endl; |
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414 cout << "Loaded " << trajectories.size() << " trajectories in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl; |
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415 |
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416 std::shared_ptr<Trajectory<cv::Point2f> > trajectory; |
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417 c_start = std::clock(); |
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418 for (unsigned int i = 0; i<trajectories.size(); ++i) { |
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419 success = trajectoryDB->read(trajectory, i, "positions"); |
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420 } |
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421 c_end = std::clock(); |
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422 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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423 |
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424 trajectoryDB->endTransaction(); |
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425 trajectoryDB->disconnect(); |
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426 } |
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427 |
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428 int main(int argc, char *argv[]) { |
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429 KLTFeatureTrackingParameters params(argc, argv); |
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430 cout << params.parameterDescription << endl; |
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431 |
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432 if (params.trackFeatures) { |
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433 cout << "The program tracks features" << endl; |
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434 trackFeatures(params); |
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435 } else if (params.groupFeatures) { |
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436 cout << "The program groups features" << endl; |
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437 groupFeatures(params); |
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438 } else if (params.loadingTime) { |
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439 cout << "The program reports loading times" << endl; |
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440 loadingTimes(params); |
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441 } else { |
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442 cout << "Main option missing or misspelt" << endl; |
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443 } |
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444 |
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445 return 0; |
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446 } |
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447 |
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448 /* ------------------ DOCUMENTATION ------------------ */ |
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449 |
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450 |
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451 /*! \mainpage |
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452 |
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453 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are: |
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454 |
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455 - \ref feature_based_tracking |
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456 |
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457 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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458 |
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459 */ |
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460 |
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461 /*! \page feature_based_tracking Feature-based Tracking: User Manual |
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462 |
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463 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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464 |
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465 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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466 |
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467 \section License |
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468 |
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469 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license). |
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470 |
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471 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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472 |
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473 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net. |
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474 |
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475 */ |