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annotate c/feature-based-tracking.cpp @ 165:50964af05a80

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solved issue with header inclusion
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 29 Sep 2011 03:12:59 -0400
parents 76610dcf3b8d
children 4eb13ed73d84
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 <list>
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21 #include <vector>
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22
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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 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 BruteForceMatcher<Hamming> descMatcher;
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74 vector<DMatch> matches;
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75 Size videoSize;
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77 // if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) // if no parameter or number parameter
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78 // capture.open(argc == 2 ? argv[1][0] - '0' : 0);
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79 // else if( argc >= 2 )
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80 // {
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81 // capture.open(argv[1]);
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82 // if( capture.isOpened() )
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83 // videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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84 // cout << "Video " << argv[1] <<
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85 // ": width=" << videoSize.width <<
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86 // ", height=" << videoSize.height <<
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87 // ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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88 // 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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89 // {
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90 // sscanf(argv[2], "%d", &params.frame1);
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91 // cout << "seeking to frame #" << params.frame1 << endl;
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92 // //cap.set(CV_CAP_PROP_POS_FRAMES, pos);
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93 // for (int i=0; i<params.frame1; i++)
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94 // capture >> frame;
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95 // }
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96 // }
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97
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98 VideoCapture capture;
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99 capture.open(params.videoFilename);
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100 if(capture.isOpened()) {
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101 videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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102 cout << "Video " << params.videoFilename <<
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103 ": width=" << videoSize.width <<
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104 ", height=" << videoSize.height <<
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105 ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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106 } else {
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107 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl;
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108 exit(0);
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109 }
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110 // if (!capture.isOpened())
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111 // {
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112 // //help(argv);
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113 // cout << "capture device " << argv[1] << " failed to open!" << endl;
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114 // return 1;
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115 // }
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116
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117 Mat mask = imread(params.maskFilename, 0);
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118 if (mask.empty())
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119 mask = Mat::ones(videoSize, CV_8UC1);
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121 boost::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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122 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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123 trajectoryDB->connect(params.databaseFilename.c_str());
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124 trajectoryDB->createTable("positions");
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125 trajectoryDB->createTable("velocities");
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126 trajectoryDB->beginTransaction();
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diff changeset
127
124
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diff changeset
128 vector<KeyPoint> prevKpts, currKpts;
130
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129 vector<Point2f> prevPts, currPts, newPts;
127
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130 vector<uchar> status;
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diff changeset
131 vector<float> errors;
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diff changeset
132 Mat prevDesc, currDesc;
128
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133
140
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diff changeset
134 vector<FeatureTrajectoryPtr> lostFeatures;
132
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diff changeset
135 vector<FeaturePointMatch> featurePointMatches;
163
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diff changeset
136
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diff changeset
137 FeatureGraph graph(params.mmConnectionDistance, params.mmSegmentationDistance);
130
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diff changeset
138
133
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139 int key = '?';
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140 unsigned int savedFeatureId=0;
164
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diff changeset
141 Mat frame, currentFrameBW, previousFrameBW;
141
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diff changeset
142 for (int frameNum = params.frame1; ((frameNum-params.frame1 < params.nFrames) || (params.nFrames < 0)) && !::interruptionKey(key); frameNum++) {
121
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diff changeset
143 capture >> frame;
134
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144 cout << frameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl;
145
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diff changeset
145 int emptyFrameNum = 0;
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diff changeset
146 while (frame.empty()) {
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147 cerr << "empty frame " << emptyFrameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES)<< endl;
123
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diff changeset
148 capture >> frame;//break;
145
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diff changeset
149 emptyFrameNum++;
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diff changeset
150 if (emptyFrameNum>=3000)
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diff changeset
151 exit(0);
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152 }
121
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153
127
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diff changeset
154 cvtColor(frame, currentFrameBW, CV_RGB2GRAY);
130
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155
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diff changeset
156 // "normal" feature detectors: detect features here
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157 // detector.detect(currentFrameBW, currKpts); // see video_homography c++ sample
121
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158
128
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159 if (!prevPts.empty()) {
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160 //::keyPoints2Points(prevKpts, prevPts);
127
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161 currPts.clear();
137
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diff changeset
162 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
163 /// \todo try calcOpticalFlowFarneback
128
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164
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diff changeset
165 vector<Point2f> trackedPts;
132
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166 vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin();
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diff changeset
167 while (iter != featurePointMatches.end()) {
135
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168 bool deleteFeature = false;
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169
132
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diff changeset
170 if (status[iter->pointNum]) {
147
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diff changeset
171 iter->feature->addPoint(frameNum, currPts[iter->pointNum], homography);
135
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diff changeset
172
139
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diff changeset
173 deleteFeature |= iter->feature->smallDisplacement(params.nDisplacements, minTotalFeatureDisplacement)
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174 || !iter->feature->motionSmooth(params.accelerationBound, params.deviationBound);
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diff changeset
175 if (deleteFeature)
138
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diff changeset
176 iter->feature->shorten();
139
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177 } else
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178 deleteFeature = true;
135
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179
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180 if (deleteFeature) {
134
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181 if (iter->feature->length() >= params.minFeatureTime) {
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182 iter->feature->setId(savedFeatureId);
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diff changeset
183 savedFeatureId++;
140
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diff changeset
184 lostFeatures.push_back(iter->feature);
134
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185 }
132
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diff changeset
186 iter = featurePointMatches.erase(iter);
138
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diff changeset
187 } else {
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188 trackedPts.push_back(currPts[iter->pointNum]);
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189 iter->pointNum = trackedPts.size()-1;
135
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diff changeset
190 iter++;
138
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191 }
132
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192 }
128
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193 currPts = trackedPts;
132
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diff changeset
194 assert(currPts.size() == featurePointMatches.size());
142
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195 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities");
134
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diff changeset
196
139
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diff changeset
197 if (params.display) {
134
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198 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches)
147
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diff changeset
199 fp.feature->draw(frame, invHomography, Colors::red());
139
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diff changeset
200 }
132
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diff changeset
201 //drawOpticalFlow(prevPts, currPts, status, frame);
134
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diff changeset
202
127
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diff changeset
203 // cout << matches.size() << " matches" << endl;
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diff changeset
204 // descMatcher.match(currDesc, prevDesc, matches);
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diff changeset
205 // cout << matches.size() << " matches" << endl;
128
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diff changeset
206 //drawMatchesRelative(prevKpts, currKpts, matches, frame);
125
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diff changeset
207 }
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diff changeset
208
128
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diff changeset
209 // adding new features, using mask around existing feature positions
146
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diff changeset
210 Mat featureMask = mask.clone();
128
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diff changeset
211 for (unsigned int n=0;n<currPts.size(); n++)
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diff changeset
212 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
213 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
214 featureMask.at<uchar>(i,j)=0;
130
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diff changeset
215 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.windowSize, params.useHarrisDetector, params.k);
132
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diff changeset
216 BOOST_FOREACH(Point2f p, newPts) { //for (unsigned int i=0; i<newPts.size(); i++) {
147
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diff changeset
217 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p, homography));
132
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diff changeset
218 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size()));
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diff changeset
219 currPts.push_back(p);
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diff changeset
220 }
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diff changeset
221 // currPts.insert(currPts.end(), newPts.begin(), newPts.end());
130
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diff changeset
222 //::keyPoints2Points(currKpts, currPts, false);
128
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diff changeset
223
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diff changeset
224 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location
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diff changeset
225
134
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diff changeset
226 if (params.display) {
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diff changeset
227 imshow("frame", frame);
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diff changeset
228 imshow("mask", featureMask*256);
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diff changeset
229 key = waitKey(2);
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diff changeset
230 }
127
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diff changeset
231 previousFrameBW = currentFrameBW.clone();
128
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diff changeset
232 prevPts = currPts;
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diff changeset
233 //prevKpts = currKpts;
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diff changeset
234 //currDesc.copyTo(prevDesc);
121
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diff changeset
235 }
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diff changeset
236
142
a3532db00c28 added code to write velocities
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diff changeset
237 trajectoryDB->endTransaction();
136
0f790de9437e renamed Feature to Motion files and added code to test blob db
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diff changeset
238 trajectoryDB->disconnect();
164
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diff changeset
239 }
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diff changeset
240
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diff changeset
241 int main(int argc, char *argv[]) {
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diff changeset
242 // BriefDescriptorExtractor brief(32);
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diff changeset
243 // const int DESIRED_FTRS = 500;
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diff changeset
244 // GridAdaptedFeatureDetector detector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4);
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parents: 163
diff changeset
245
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diff changeset
246 KLTFeatureTrackingParameters params(argc, argv);
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diff changeset
247 cout << params.parameterDescription << endl;
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diff changeset
248
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diff changeset
249 if (params.trackFeatures)
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diff changeset
250 trackFeatures(params);
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diff changeset
251 else if (params.groupFeatures) {
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diff changeset
252 cout << "group" << endl;
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diff changeset
253
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254 boost::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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255 //TODO write generic methods for blob and list versions TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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256 bool success = trajectoryDB->connect(params.databaseFilename.c_str());
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257 vector<boost::shared_ptr<Trajectory<Point2f> > > trajectories;
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258 cout << trajectories.size() << endl;
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259 success = trajectoryDB->read(trajectories, "positions");
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260 cout << trajectories.size() << endl;
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261 cout << trajectories[0]->size() << endl;
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262 //cout << trajectories[0]->getPoint(0) << endl;
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263 trajectoryDB->endTransaction();
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264 trajectoryDB->disconnect();
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265 }
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266
117
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267 return 0;
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268 }
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269
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270 /* ------------------ DOCUMENTATION ------------------ */
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271
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272
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273 /*! \mainpage
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274
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275 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are:
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276
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277 - \ref feature_based_tracking
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278
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279 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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280
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281 */
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282
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283 /*! \page feature_based_tracking Feature-based Tracking: User Manual
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284
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285 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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286
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287 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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288
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289 \section License
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290
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291 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license).
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292
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293 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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294
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295 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net.
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296
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297 */