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annotate c/feature-based-tracking.cpp @ 174:ec9734015d53

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tested loading trajectory by id numbers
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 26 Oct 2011 17:46:11 -0400
parents e508bb0cbb64
children a234a5e818f3
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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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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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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16 #include <boost/shared_ptr.hpp>
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17 #include <boost/foreach.hpp>
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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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23 using namespace std;
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24 using namespace cv;
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26 void drawMatchesRelative(const vector<KeyPoint>& train, const vector<KeyPoint>& query, std::vector<cv::DMatch>& matches, Mat& img) {
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27 for (int i = 0; i < (int)matches.size(); i++)
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28 {
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29 Point2f pt_new = query[matches[i].queryIdx].pt;
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30 Point2f pt_old = train[matches[i].trainIdx].pt;
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31 Point2f dist = pt_new - pt_old;
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32 if (norm(dist) < 20) {
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33 line(img, pt_new, pt_old, Scalar(125, 255, 125), 1);
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34 circle(img, pt_old, 2, Scalar(255, 0, 125), 1);
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35 }
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36 }
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37 }
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39 void drawOpticalFlow(const vector<Point2f>& prevPts, const vector<Point2f>& currPts, const vector<uchar> status, Mat& img) {
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40 for (unsigned int i=0; i<status.size(); i++) {
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41 if (status[i]) {
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42 line(img, prevPts[i], currPts[i], Scalar(125, 255, 125), 1);
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43 circle(img, prevPts[i], 2, Scalar(255, 0, 125), 1);
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44 }
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45 }
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46 }
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48 struct FeaturePointMatch {
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49 FeatureTrajectoryPtr feature;
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50 int pointNum;
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51
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52 FeaturePointMatch(FeatureTrajectoryPtr _feature, const int& _pointNum):
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53 feature(_feature), pointNum(_pointNum) {}
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54 };
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55
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56 inline void saveFeatures(vector<FeatureTrajectoryPtr>& features, TrajectoryDBAccess<Point2f>& db, const string& positionsTableName, const string& velocitiesTableName, const unsigned int& minNFeatures = 0) {
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57 /// \todo smoothing
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58 if (features.size() >= minNFeatures) {
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59 BOOST_FOREACH(FeatureTrajectoryPtr f, features) f->write(db, positionsTableName, velocitiesTableName);
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60 features.clear();
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61 }
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62 }
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64 void trackFeatures(const KLTFeatureTrackingParameters& params) {
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65 // BriefDescriptorExtractor brief(32);
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66 // const int DESIRED_FTRS = 500;
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67 // GridAdaptedFeatureDetector detector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4);
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69 Mat homography = ::loadMat(params.homographyFilename, " ");
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70 Mat invHomography;
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71 if (params.display && !homography.empty())
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72 invHomography = homography.inv();
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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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77 BruteForceMatcher<Hamming> descMatcher;
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78 vector<DMatch> matches;
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79 Size videoSize;
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81 // if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) // if no parameter or number parameter
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82 // capture.open(argc == 2 ? argv[1][0] - '0' : 0);
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83 // else if( argc >= 2 )
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84 // {
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85 // capture.open(argv[1]);
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86 // if( capture.isOpened() )
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87 // videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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88 // cout << "Video " << argv[1] <<
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89 // ": width=" << videoSize.width <<
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90 // ", height=" << videoSize.height <<
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91 // ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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92 // if( argc > 2 && isdigit(argv[2][0]) ) // could be used to reach first frame, dumping library messages to log file (2> /tmp/log.txt)
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93 // {
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94 // sscanf(argv[2], "%d", &params.frame1);
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95 // cout << "seeking to frame #" << params.frame1 << endl;
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96 // //cap.set(CV_CAP_PROP_POS_FRAMES, pos);
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97 // for (int i=0; i<params.frame1; i++)
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98 // capture >> frame;
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99 // }
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100 // }
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101
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102 VideoCapture capture;
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103 capture.open(params.videoFilename);
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104 if(capture.isOpened()) {
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105 videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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106 cout << "Video " << params.videoFilename <<
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107 ": width=" << videoSize.width <<
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108 ", height=" << videoSize.height <<
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109 ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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110 } else {
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111 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl;
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112 exit(0);
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113 }
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114 // if (!capture.isOpened())
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115 // {
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116 // //help(argv);
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117 // cout << "capture device " << argv[1] << " failed to open!" << endl;
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118 // return 1;
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119 // }
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120
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121 Mat mask = imread(params.maskFilename, 0);
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122 if (mask.empty())
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123 mask = Mat::ones(videoSize, CV_8UC1);
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125 boost::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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126 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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diff changeset
127 trajectoryDB->connect(params.databaseFilename.c_str());
142
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diff changeset
128 trajectoryDB->createTable("positions");
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diff changeset
129 trajectoryDB->createTable("velocities");
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diff changeset
130 trajectoryDB->beginTransaction();
133
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diff changeset
131
124
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diff changeset
132 vector<KeyPoint> prevKpts, currKpts;
130
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133 vector<Point2f> prevPts, currPts, newPts;
127
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diff changeset
134 vector<uchar> status;
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diff changeset
135 vector<float> errors;
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diff changeset
136 Mat prevDesc, currDesc;
128
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137
140
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diff changeset
138 vector<FeatureTrajectoryPtr> lostFeatures;
132
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diff changeset
139 vector<FeaturePointMatch> featurePointMatches;
163
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diff changeset
140
cde87a07eb58 added graph structures
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diff changeset
141 FeatureGraph graph(params.mmConnectionDistance, params.mmSegmentationDistance);
130
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diff changeset
142
133
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143 int key = '?';
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diff changeset
144 unsigned int savedFeatureId=0;
164
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diff changeset
145 Mat frame, currentFrameBW, previousFrameBW;
141
6f10a227486c modifications to get nframes option working on the command line
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diff changeset
146 for (int frameNum = params.frame1; ((frameNum-params.frame1 < params.nFrames) || (params.nFrames < 0)) && !::interruptionKey(key); frameNum++) {
121
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diff changeset
147 capture >> frame;
134
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diff changeset
148 cout << frameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl;
145
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diff changeset
149 int emptyFrameNum = 0;
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diff changeset
150 while (frame.empty()) {
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diff changeset
151 cerr << "empty frame " << emptyFrameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES)<< endl;
123
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diff changeset
152 capture >> frame;//break;
145
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diff changeset
153 emptyFrameNum++;
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diff changeset
154 if (emptyFrameNum>=3000)
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diff changeset
155 exit(0);
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diff changeset
156 }
121
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diff changeset
157
127
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diff changeset
158 cvtColor(frame, currentFrameBW, CV_RGB2GRAY);
130
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diff changeset
159
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diff changeset
160 // "normal" feature detectors: detect features here
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161 // detector.detect(currentFrameBW, currKpts); // see video_homography c++ sample
121
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diff changeset
162
128
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163 if (!prevPts.empty()) {
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164 //::keyPoints2Points(prevKpts, prevPts);
127
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diff changeset
165 currPts.clear();
137
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diff changeset
166 calcOpticalFlowPyrLK(previousFrameBW, currentFrameBW, prevPts, currPts, status, errors, window, params.pyramidLevel, TermCriteria(3 /*static_cast<int>(TermCriteria::COUNT)+static_cast<int>(TermCriteria::EPS)*/, params.maxNumberTrackingIterations, params.minTrackingError), 0.5 /* unused */, 0); // OPTFLOW_USE_INITIAL_FLOW
154
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diff changeset
167 /// \todo try calcOpticalFlowFarneback
128
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diff changeset
168
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diff changeset
169 vector<Point2f> trackedPts;
132
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diff changeset
170 vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin();
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diff changeset
171 while (iter != featurePointMatches.end()) {
135
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diff changeset
172 bool deleteFeature = false;
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173
132
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diff changeset
174 if (status[iter->pointNum]) {
147
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diff changeset
175 iter->feature->addPoint(frameNum, currPts[iter->pointNum], homography);
135
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diff changeset
176
139
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diff changeset
177 deleteFeature |= iter->feature->smallDisplacement(params.nDisplacements, minTotalFeatureDisplacement)
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178 || !iter->feature->motionSmooth(params.accelerationBound, params.deviationBound);
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diff changeset
179 if (deleteFeature)
138
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diff changeset
180 iter->feature->shorten();
139
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181 } else
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diff changeset
182 deleteFeature = true;
135
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diff changeset
183
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diff changeset
184 if (deleteFeature) {
134
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diff changeset
185 if (iter->feature->length() >= params.minFeatureTime) {
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diff changeset
186 iter->feature->setId(savedFeatureId);
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diff changeset
187 savedFeatureId++;
140
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diff changeset
188 lostFeatures.push_back(iter->feature);
134
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189 }
132
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diff changeset
190 iter = featurePointMatches.erase(iter);
138
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diff changeset
191 } else {
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diff changeset
192 trackedPts.push_back(currPts[iter->pointNum]);
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diff changeset
193 iter->pointNum = trackedPts.size()-1;
135
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diff changeset
194 iter++;
138
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195 }
132
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diff changeset
196 }
128
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diff changeset
197 currPts = trackedPts;
132
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diff changeset
198 assert(currPts.size() == featurePointMatches.size());
142
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diff changeset
199 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities");
134
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diff changeset
200
139
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diff changeset
201 if (params.display) {
134
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diff changeset
202 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches)
147
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diff changeset
203 fp.feature->draw(frame, invHomography, Colors::red());
139
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diff changeset
204 }
132
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diff changeset
205 //drawOpticalFlow(prevPts, currPts, status, frame);
134
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diff changeset
206
127
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diff changeset
207 // cout << matches.size() << " matches" << endl;
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diff changeset
208 // descMatcher.match(currDesc, prevDesc, matches);
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diff changeset
209 // cout << matches.size() << " matches" << endl;
128
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diff changeset
210 //drawMatchesRelative(prevKpts, currKpts, matches, frame);
125
28907fde9855 work on klt tracker (problem on computer at poly)
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parents: 124
diff changeset
211 }
28907fde9855 work on klt tracker (problem on computer at poly)
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diff changeset
212
128
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diff changeset
213 // adding new features, using mask around existing feature positions
146
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diff changeset
214 Mat featureMask = mask.clone();
128
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diff changeset
215 for (unsigned int n=0;n<currPts.size(); n++)
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diff changeset
216 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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diff changeset
217 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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diff changeset
218 featureMask.at<uchar>(i,j)=0;
130
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diff changeset
219 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.windowSize, params.useHarrisDetector, params.k);
132
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diff changeset
220 BOOST_FOREACH(Point2f p, newPts) { //for (unsigned int i=0; i<newPts.size(); i++) {
147
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diff changeset
221 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p, homography));
132
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diff changeset
222 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size()));
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diff changeset
223 currPts.push_back(p);
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diff changeset
224 }
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diff changeset
225 // currPts.insert(currPts.end(), newPts.begin(), newPts.end());
130
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diff changeset
226 //::keyPoints2Points(currKpts, currPts, false);
128
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diff changeset
227
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diff changeset
228 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location
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diff changeset
229
134
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diff changeset
230 if (params.display) {
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diff changeset
231 imshow("frame", frame);
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diff changeset
232 imshow("mask", featureMask*256);
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diff changeset
233 key = waitKey(2);
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diff changeset
234 }
127
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diff changeset
235 previousFrameBW = currentFrameBW.clone();
128
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diff changeset
236 prevPts = currPts;
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diff changeset
237 //prevKpts = currKpts;
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diff changeset
238 //currDesc.copyTo(prevDesc);
121
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diff changeset
239 }
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diff changeset
240
142
a3532db00c28 added code to write velocities
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diff changeset
241 trajectoryDB->endTransaction();
136
0f790de9437e renamed Feature to Motion files and added code to test blob db
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parents: 135
diff changeset
242 trajectoryDB->disconnect();
164
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parents: 163
diff changeset
243 }
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parents: 163
diff changeset
244
169
5f705809d37a created groupFeatures function
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parents: 168
diff changeset
245 void groupFeatures(const KLTFeatureTrackingParameters& params) {
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diff changeset
246 cout << "group" << endl;
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diff changeset
247
5f705809d37a created groupFeatures function
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diff changeset
248 boost::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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diff changeset
249 //TODO write generic methods for blob and list versions TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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diff changeset
250 bool success = trajectoryDB->connect(params.databaseFilename.c_str());
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diff changeset
251 vector<boost::shared_ptr<Trajectory<Point2f> > > trajectories;
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diff changeset
252 cout << trajectories.size() << endl;
174
ec9734015d53 tested loading trajectory by id numbers
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diff changeset
253 // std::clock_t c_start = std::clock();
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254 // success = trajectoryDB->read(trajectories, "positions"); // TODO load velocities as well in a FeatureTrajectory object // attention, velocities lack the first instant
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255 // std::clock_t c_end = std::clock();
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256 // cout << "Loaded " << trajectories.size() << " trajectories in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl;
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257
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258 // boost::shared_ptr<Trajectory<cv::Point2f> > trajectory;
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259 // c_start = std::clock();
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260 // for (unsigned int i = 0; i<trajectories.size(); ++i) {
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261 // success = trajectoryDB->read(trajectory, i, "positions");
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262 // }
174
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263 // c_end = std::clock();
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264 // 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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265
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266 trajectoryDB->createViewInstants("first");
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267 trajectoryDB->createViewInstants("last");
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268
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269 // main loop
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270 // TODO version que l'on peut interrompre ?
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271 for (int frameNum = params.frame1; ((frameNum-params.frame1 < params.nFrames) || (params.nFrames < 0)); frameNum++) {
174
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272 vector<int> trajectoryIds;
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273 success = trajectoryDB->trajectoryIdStartingAt(trajectoryIds, frameNum);
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274 cout << "frame " << frameNum << " " << success << endl;
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275 cout << trajectoryIds.size() << " trajectories " << endl;
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276 BOOST_FOREACH(int trajectoryId, trajectoryIds) {
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277 //cout << trajectoryId << " " << endl;
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278 boost::shared_ptr<Trajectory<cv::Point2f> > trajectory;
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279 success = trajectoryDB->read(trajectory, trajectoryId, "positions"); // velocities
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280 stringstream ss;ss << *trajectory; cout << ss.str() << endl;
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281 }
172
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282
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283 // should the trajectory be loaded one by one? yes
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284
174
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285 }
169
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286
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287 trajectoryDB->endTransaction();
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288 trajectoryDB->disconnect();
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289 }
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290
164
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291 int main(int argc, char *argv[]) {
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292 KLTFeatureTrackingParameters params(argc, argv);
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293 cout << params.parameterDescription << endl;
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294
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295 if (params.trackFeatures)
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296 trackFeatures(params);
169
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297 else if (params.groupFeatures)
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298 groupFeatures(params);
164
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299
117
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300 return 0;
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301 }
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302
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303 /* ------------------ DOCUMENTATION ------------------ */
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304
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305
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306 /*! \mainpage
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307
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308 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are:
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309
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310 - \ref feature_based_tracking
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311
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312 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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313
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314 */
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315
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316 /*! \page feature_based_tracking Feature-based Tracking: User Manual
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317
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318 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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319
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320 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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321
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322 \section License
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323
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324 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license).
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325
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326 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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327
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328 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net.
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329
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330 */