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annotate c/feature-based-tracking.cpp @ 856:e310577cc0b8
updated function (url) for weather data
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Wed, 05 Oct 2016 13:31:42 -0400 |
parents | daa992ac6b44 |
children | a71455bd8367 |
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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 |
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17 #include <boost/foreach.hpp> |
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18 |
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19 #include <iostream> |
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20 #include <vector> |
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21 #include <ctime> |
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22 #include <cmath> |
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23 #include <memory> |
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24 #include <limits> |
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25 |
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26 using namespace std; |
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27 using namespace cv; |
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28 |
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29 void drawMatchesRelative(const vector<KeyPoint>& train, const vector<KeyPoint>& query, std::vector<cv::DMatch>& matches, Mat& img) { |
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30 for (int i = 0; i < (int)matches.size(); i++) |
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31 { |
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32 Point2f pt_new = query[matches[i].queryIdx].pt; |
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33 Point2f pt_old = train[matches[i].trainIdx].pt; |
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34 Point2f dist = pt_new - pt_old; |
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35 if (norm(dist) < 20) { |
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36 line(img, pt_new, pt_old, Scalar(125, 255, 125), 1); |
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37 circle(img, pt_old, 2, Scalar(255, 0, 125), 1); |
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38 } |
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39 } |
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40 } |
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41 |
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42 void drawOpticalFlow(const vector<Point2f>& prevPts, const vector<Point2f>& currPts, const vector<uchar> status, Mat& img) { |
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43 for (unsigned int i=0; i<status.size(); i++) { |
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44 if (status[i]) { |
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45 line(img, prevPts[i], currPts[i], Scalar(125, 255, 125), 1); |
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46 circle(img, prevPts[i], 2, Scalar(255, 0, 125), 1); |
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47 } |
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48 } |
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49 } |
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50 |
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51 struct FeaturePointMatch { |
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52 FeatureTrajectoryPtr feature; |
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53 int pointNum; |
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54 |
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55 FeaturePointMatch(FeatureTrajectoryPtr _feature, const int& _pointNum): |
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56 feature(_feature), pointNum(_pointNum) {} |
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57 }; |
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58 |
480 | 59 inline void saveFeatures(vector<FeatureTrajectoryPtr>& features, TrajectoryDBAccess<Point2f>& db, const string& positionsTableName, const string& velocitiesTableName) { |
60 BOOST_FOREACH(FeatureTrajectoryPtr f, features) f->write(db, positionsTableName, velocitiesTableName); | |
61 features.clear(); | |
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62 } |
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63 |
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64 void trackFeatures(const KLTFeatureTrackingParameters& params) { |
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65 Mat homography = ::loadMat(params.homographyFilename, " "); |
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66 Mat invHomography; |
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67 if (params.display && !homography.empty()) |
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68 invHomography = homography.inv(); |
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69 |
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70 float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement; |
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71 Size window = Size(params.windowSize, params.windowSize); |
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72 |
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73 int interpolationMethod = -1; |
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74 if (params.interpolationMethod == 0) |
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75 interpolationMethod = INTER_NEAREST; |
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76 else if (params.interpolationMethod == 1) |
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77 interpolationMethod = INTER_LINEAR; |
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78 else if (params.interpolationMethod == 2) |
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79 interpolationMethod = INTER_CUBIC; |
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80 else if (params.interpolationMethod == 3) |
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81 interpolationMethod = INTER_LANCZOS4; |
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82 else |
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83 cout << "Unsupported option " << interpolationMethod << " for interpolation method" << endl; |
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84 |
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85 // BruteForceMatcher<Hamming> descMatcher; |
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86 // vector<DMatch> matches; |
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87 |
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88 if(params.videoFilename.empty()) { |
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89 cout << "Empty video filename. Exiting." << endl; |
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90 exit(0); |
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91 } |
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92 |
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93 VideoCapture capture(params.videoFilename); |
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94 if(!capture.isOpened()) { |
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95 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl; |
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96 exit(0); |
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97 } |
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98 |
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99 Size videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT)); |
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100 unsigned int nFrames = capture.get(CV_CAP_PROP_FRAME_COUNT); |
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101 if (nFrames <= 0) { |
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102 cout << "Guessing that the number of frames could not be read: " << nFrames << endl; |
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103 nFrames = numeric_limits<int>::max(); |
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104 cout << "Setting arbitrarily high number for testing: " << nFrames << endl; |
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105 } |
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106 |
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107 cout << "Video " << params.videoFilename << |
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108 ": width=" << videoSize.width << |
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109 ", height=" << videoSize.height << |
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110 ", nframes=" << nFrames << endl; |
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111 |
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112 Mat map1, map2; |
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113 if (params.undistort) { |
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114 Mat intrinsicCameraMatrix = ::loadMat(params.intrinsicCameraFilename, " "); |
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115 Mat newIntrinsicCameraMatrix = intrinsicCameraMatrix.clone(); |
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116 videoSize = Size(static_cast<int>(round(videoSize.width*params.undistortedImageMultiplication)), static_cast<int>(round(videoSize.height*params.undistortedImageMultiplication))); |
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117 newIntrinsicCameraMatrix.at<float>(0,2) = videoSize.width/2.; |
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118 newIntrinsicCameraMatrix.at<float>(1,2) = videoSize.height/2.; |
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119 initUndistortRectifyMap(intrinsicCameraMatrix, params.distortionCoefficients, Mat::eye(3,3, CV_32FC1), newIntrinsicCameraMatrix, videoSize, CV_32FC1, map1, map2); |
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120 |
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121 cout << "Undistorted width=" << videoSize.width << |
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122 ", height=" << videoSize.height << endl; |
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123 } |
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124 |
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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 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>(); |
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133 trajectoryDB->connect(params.databaseFilename.c_str()); |
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134 trajectoryDB->createTable("positions"); |
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135 trajectoryDB->createTable("velocities"); |
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136 trajectoryDB->beginTransaction(); |
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137 |
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138 std::vector<KeyPoint> prevKpts, currKpts; |
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139 std::vector<Point2f> prevPts, currPts, newPts; |
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140 std::vector<uchar> status; |
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141 std::vector<float> errors; |
127
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142 Mat prevDesc, currDesc; |
128
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143 |
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144 std::vector<FeatureTrajectoryPtr> lostFeatures; |
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145 std::vector<FeaturePointMatch> featurePointMatches; |
163
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146 |
133
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147 int key = '?'; |
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148 unsigned int savedFeatureId=0; |
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149 Mat frame = Mat::zeros(1, 1, CV_8UC1), currentFrameBW, previousFrameBW, undistortedFrame; |
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150 |
278
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151 unsigned int lastFrameNum = nFrames; |
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152 if (params.nFrames > 0) |
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153 lastFrameNum = MIN(params.frame1+static_cast<unsigned int>(params.nFrames), nFrames); |
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154 |
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155 capture.set(CV_CAP_PROP_POS_FRAMES, params.frame1); |
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156 for (unsigned int frameNum = params.frame1; (frameNum < lastFrameNum) && !::interruptionKey(key); frameNum++) { |
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157 capture >> frame; |
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158 if (frame.empty()) { |
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159 cout << "Empty frame " << frameNum << ", breaking (" << frame.empty() << " [" << frame.size().width << "x" << frame.size().height << "])" << endl; |
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160 break; |
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161 } else if (frameNum%50 ==0) |
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162 cout << "frame " << frameNum << endl; |
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163 |
655
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164 if (params.undistort) { |
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165 remap(frame, undistortedFrame, map1, map2, interpolationMethod, BORDER_CONSTANT, 0.); |
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166 frame = undistortedFrame; |
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167 |
655
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168 if (frame.size() != videoSize) { |
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169 cout << "Different frame size " << frameNum << ", breaking ([" << frame.size().width << "x" << frame.size().height << "])" << endl; |
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170 break; |
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171 } |
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172 } |
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173 |
655
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174 cvtColor(frame, currentFrameBW, CV_RGB2GRAY); |
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175 |
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176 if (!prevPts.empty()) { |
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177 currPts.clear(); |
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178 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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179 /// \todo try calcOpticalFlowFarneback |
128
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180 |
655
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181 std::vector<Point2f> trackedPts; |
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182 std::vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); |
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183 while (iter != featurePointMatches.end()) { |
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184 bool deleteFeature = false; |
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185 |
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186 int currPtX = static_cast<int>(floor(currPts[iter->pointNum].x)); |
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187 int currPtY = static_cast<int>(floor(currPts[iter->pointNum].y)); |
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188 if ((status[iter->pointNum] =!0) && |
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189 (currPtX >= 0) && (currPtX < videoSize.width) && |
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190 (currPtY >= 0) && (currPtY < videoSize.height) && |
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191 (mask.at<uchar>(currPtY, currPtX) != 0)) { |
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192 iter->feature->addPoint(frameNum, currPts[iter->pointNum], homography); |
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193 |
655
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194 deleteFeature = iter->feature->isDisplacementSmall(params.nDisplacements, minTotalFeatureDisplacement) |
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195 || !iter->feature->isMotionSmooth(params.accelerationBound, params.deviationBound); |
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196 if (deleteFeature) |
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197 iter->feature->shorten(); |
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198 } else |
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199 deleteFeature = true; |
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200 |
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201 if (deleteFeature) { |
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202 if (iter->feature->length() >= params.minFeatureTime) { |
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203 iter->feature->setId(savedFeatureId); |
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204 savedFeatureId++; |
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205 iter->feature->movingAverage(params.nFramesSmoothing); |
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206 lostFeatures.push_back(iter->feature); |
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207 } |
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208 iter = featurePointMatches.erase(iter); |
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209 } else { |
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210 trackedPts.push_back(currPts[iter->pointNum]); |
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211 iter->pointNum = trackedPts.size()-1; |
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212 iter++; |
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213 } |
125
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214 } |
655
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215 currPts = trackedPts; |
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216 assert(currPts.size() == featurePointMatches.size()); |
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217 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities"); |
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218 |
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219 if (params.display) { |
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220 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches) |
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221 fp.feature->draw(frame, invHomography, Colors::red()); |
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222 } |
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223 } |
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224 |
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225 // adding new features, using mask around existing feature positions |
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226 Mat featureMask = mask.clone(); |
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227 for (unsigned int n=0;n<currPts.size(); n++) |
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228 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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229 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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230 featureMask.at<uchar>(i,j)=0; |
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231 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.blockSize, params.useHarrisDetector, params.k); |
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232 BOOST_FOREACH(Point2f p, newPts) { |
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233 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p, homography)); |
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234 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size())); |
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235 currPts.push_back(p); |
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236 } |
128
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237 |
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238 if (params.display) { |
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239 imshow("mask", featureMask*256); |
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240 imshow("frame", frame); |
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241 key = waitKey(2); |
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242 } |
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243 previousFrameBW = currentFrameBW.clone(); |
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244 prevPts = currPts; |
480 | 245 } |
246 | |
247 // save the remaining currently tracked features | |
248 std::vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); | |
249 while (iter != featurePointMatches.end()) { | |
250 if (iter->feature->length() >= params.minFeatureTime) { | |
251 iter->feature->setId(savedFeatureId); | |
252 savedFeatureId++; | |
481
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253 iter->feature->movingAverage(params.nFramesSmoothing); |
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254 iter->feature->write(*trajectoryDB, "positions", "velocities"); |
480 | 255 } |
256 iter++; | |
257 } | |
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258 |
142
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259 trajectoryDB->endTransaction(); |
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260 trajectoryDB->disconnect(); |
164
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261 } |
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262 |
169
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263 void groupFeatures(const KLTFeatureTrackingParameters& params) { |
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264 std::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
169
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265 bool success = trajectoryDB->connect(params.databaseFilename.c_str()); |
202
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266 trajectoryDB->createObjectTable("objects", "objects_features"); |
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267 unsigned int savedObjectId=0; |
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268 |
225
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269 trajectoryDB->createInstants("table"); |
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270 //trajectoryDB->createIndex("positions","trajectory_id"); // does not seem to make loading features faster |
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271 //trajectoryDB->createIndex("velocities","trajectory_id"); |
221
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272 |
225
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273 unsigned int maxTrajectoryLength = 0; |
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274 success = trajectoryDB->maxTrajectoryLength(maxTrajectoryLength); |
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275 if (!success || maxTrajectoryLength == 0) { |
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276 cout << "problem with trajectory length " << success << endl; |
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277 exit(0); |
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278 } |
222
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279 cout << "Longest trajectory: " << maxTrajectoryLength << endl; |
219
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280 |
191
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281 FeatureGraph featureGraph(params.mmConnectionDistance, params.mmSegmentationDistance, params.minFeatureTime, params.minNFeaturesPerGroup); |
180
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282 |
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283 // main loop |
227
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284 unsigned int frameNum; |
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285 unsigned int firstFrameNum = -1, lastFrameNum = -1; |
225
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286 trajectoryDB->firstLastInstants(firstFrameNum, lastFrameNum); |
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287 firstFrameNum = MAX(firstFrameNum, params.frame1); |
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288 if (params.nFrames>0) |
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289 lastFrameNum = MIN(lastFrameNum,params.frame1+params.nFrames); |
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290 for (frameNum = firstFrameNum; frameNum<lastFrameNum; frameNum ++) { |
174
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291 vector<int> trajectoryIds; |
231
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292 success = trajectoryDB->trajectoryIdEndingAt(trajectoryIds, frameNum); |
225
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293 if (frameNum%100 ==0) |
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294 cout << "frame " << frameNum << endl; |
222
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295 #if DEBUG |
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296 cout << trajectoryIds.size() << " trajectories " << endl; |
222
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297 #endif |
174
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298 BOOST_FOREACH(int trajectoryId, trajectoryIds) { |
177
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299 FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(trajectoryId, *trajectoryDB, "positions", "velocities")); |
180
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300 featureGraph.addFeature(ft); |
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301 } |
172
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302 |
222
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303 // check for connected components |
225
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304 int lastInstant = frameNum+params.minFeatureTime-maxTrajectoryLength; |
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305 if (lastInstant > 0 && frameNum%10==0) { |
225
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306 featureGraph.connectedComponents(lastInstant); |
391
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307 vector<vector<FeatureTrajectoryPtr> > featureGroups; |
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308 featureGraph.getFeatureGroups(featureGroups); |
225
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309 for (unsigned int i=0; i<featureGroups.size(); ++i) { |
391
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310 vector<unsigned int> featureNumbers; |
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311 for (unsigned int j=0; j<featureGroups[i].size(); ++j) |
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312 featureNumbers.push_back(featureGroups[i][j]->getId()); |
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313 trajectoryDB->writeObject(savedObjectId, featureNumbers, 0 /* unknown type */, 1, string("objects"), string("objects_features")); |
225
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314 savedObjectId++; |
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315 } |
188
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316 } |
222
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317 |
225
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318 if (frameNum%100 ==0) |
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319 cout << featureGraph.informationString() << endl; |
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320 } |
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321 |
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322 // save remaining objects |
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323 featureGraph.connectedComponents(frameNum+maxTrajectoryLength+1); |
391
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324 vector<vector<FeatureTrajectoryPtr> > featureGroups; |
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325 featureGraph.getFeatureGroups(featureGroups); |
225
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326 for (unsigned int i=0; i<featureGroups.size(); ++i) { |
391
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327 vector<unsigned int> featureNumbers; |
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328 for (unsigned int j=0; j<featureGroups[i].size(); ++j) |
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329 featureNumbers.push_back(featureGroups[i][j]->getId()); |
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330 trajectoryDB->writeObject(savedObjectId, featureNumbers, 0 /* unknown */, 1, string("objects"), string("objects_features")); |
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331 savedObjectId++; |
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332 } |
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333 |
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334 trajectoryDB->endTransaction(); |
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335 trajectoryDB->disconnect(); |
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336 } |
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337 |
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338 void loadingTimes(const KLTFeatureTrackingParameters& params) { |
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339 std::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = std::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
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340 bool success = trajectoryDB->connect(params.databaseFilename.c_str()); |
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341 |
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342 vector<std::shared_ptr<Trajectory<Point2f> > > trajectories; |
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343 //cout << trajectories.size() << endl; |
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344 std::clock_t c_start = std::clock(); |
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345 success = trajectoryDB->read(trajectories, "positions"); |
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346 std::clock_t c_end = std::clock(); |
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347 if (!success) |
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348 cout << "Issue with db reading" << endl; |
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349 cout << "Loaded " << trajectories.size() << " trajectories in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl; |
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350 |
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351 std::shared_ptr<Trajectory<cv::Point2f> > trajectory; |
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352 c_start = std::clock(); |
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353 for (unsigned int i = 0; i<trajectories.size(); ++i) { |
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354 success = trajectoryDB->read(trajectory, i, "positions"); |
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355 } |
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356 c_end = std::clock(); |
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357 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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358 |
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359 trajectoryDB->endTransaction(); |
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360 trajectoryDB->disconnect(); |
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361 } |
169
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362 |
164
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363 int main(int argc, char *argv[]) { |
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364 KLTFeatureTrackingParameters params(argc, argv); |
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365 cout << params.parameterDescription << endl; |
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366 |
234
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367 if (params.trackFeatures) { |
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368 cout << "The program tracks features" << endl; |
164
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369 trackFeatures(params); |
234
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370 } else if (params.groupFeatures) { |
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371 cout << "The program groups features" << endl; |
169
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372 groupFeatures(params); |
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373 } else if (params.loadingTime) { |
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374 cout << "The program reports loading times" << endl; |
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375 loadingTimes(params); |
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376 } else { |
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377 cout << "Main option missing or misspelt" << endl; |
234
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378 } |
164
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379 |
117
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380 return 0; |
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381 } |
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382 |
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383 /* ------------------ DOCUMENTATION ------------------ */ |
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384 |
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385 |
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386 /*! \mainpage |
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387 |
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388 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are: |
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389 |
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390 - \ref feature_based_tracking |
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391 |
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392 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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393 |
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394 */ |
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395 |
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396 /*! \page feature_based_tracking Feature-based Tracking: User Manual |
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397 |
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398 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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399 |
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400 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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401 |
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402 \section License |
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403 |
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404 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license). |
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405 |
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406 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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407 |
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408 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net. |
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409 |
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410 */ |