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annotate c/feature-based-tracking.cpp @ 227:b7612c6d5702

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cleaned the code
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 27 Jun 2012 09:52:06 -0400
parents d4d3b1e8a9f1
children 23da16442433
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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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15 #include "opencv2/objdetect/objdetect.hpp"
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17 #include <boost/shared_ptr.hpp>
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18 #include <boost/foreach.hpp>
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20 #include <iostream>
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21 #include <vector>
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22 #include <ctime>
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24 using namespace std;
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25 using namespace cv;
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27 void drawMatchesRelative(const vector<KeyPoint>& train, const vector<KeyPoint>& query, std::vector<cv::DMatch>& matches, Mat& img) {
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28 for (int i = 0; i < (int)matches.size(); i++)
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29 {
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30 Point2f pt_new = query[matches[i].queryIdx].pt;
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31 Point2f pt_old = train[matches[i].trainIdx].pt;
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32 Point2f dist = pt_new - pt_old;
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33 if (norm(dist) < 20) {
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34 line(img, pt_new, pt_old, Scalar(125, 255, 125), 1);
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35 circle(img, pt_old, 2, Scalar(255, 0, 125), 1);
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36 }
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37 }
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38 }
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40 void drawOpticalFlow(const vector<Point2f>& prevPts, const vector<Point2f>& currPts, const vector<uchar> status, Mat& img) {
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41 for (unsigned int i=0; i<status.size(); i++) {
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42 if (status[i]) {
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43 line(img, prevPts[i], currPts[i], Scalar(125, 255, 125), 1);
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44 circle(img, prevPts[i], 2, Scalar(255, 0, 125), 1);
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45 }
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46 }
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47 }
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49 struct FeaturePointMatch {
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50 FeatureTrajectoryPtr feature;
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51 int pointNum;
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52
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53 FeaturePointMatch(FeatureTrajectoryPtr _feature, const int& _pointNum):
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54 feature(_feature), pointNum(_pointNum) {}
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55 };
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56
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57 inline void saveFeatures(vector<FeatureTrajectoryPtr>& features, TrajectoryDBAccess<Point2f>& db, const string& positionsTableName, const string& velocitiesTableName, const unsigned int& minNFeatures = 0) {
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58 /// \todo smoothing
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59 if (features.size() >= minNFeatures) {
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60 BOOST_FOREACH(FeatureTrajectoryPtr f, features) f->write(db, positionsTableName, velocitiesTableName);
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61 features.clear();
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62 }
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63 }
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64
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65 void trackFeatures(const KLTFeatureTrackingParameters& params) {
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66 // BriefDescriptorExtractor brief(32);
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67 // const int DESIRED_FTRS = 500;
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68 // GridAdaptedFeatureDetector detector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4);
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69
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70 Mat homography = ::loadMat(params.homographyFilename, " ");
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71 Mat invHomography;
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72 if (params.display && !homography.empty())
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73 invHomography = homography.inv();
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74
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75 float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement;
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76 Size window = Size(params.windowSize, params.windowSize);
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77
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78 // BruteForceMatcher<Hamming> descMatcher;
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79 // vector<DMatch> matches;
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80
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81 VideoCapture capture;
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82 Size videoSize;
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83 int nFrames = -1;
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84 capture.open(params.videoFilename);
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85 if(capture.isOpened()) {
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86 videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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87 nFrames = capture.get(CV_CAP_PROP_FRAME_COUNT);
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88 cout << "Video " << params.videoFilename <<
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89 ": width=" << videoSize.width <<
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90 ", height=" << videoSize.height <<
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91 ", nframes=" << nFrames << endl;
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92 } else {
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93 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl;
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94 exit(0);
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95 }
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96 // if (!capture.isOpened())
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97 // {
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98 // //help(argv);
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99 // cout << "capture device " << argv[1] << " failed to open!" << endl;
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100 // return 1;
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101 // }
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102
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103 Mat mask = imread(params.maskFilename, 0);
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104 if (mask.empty())
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105 mask = Mat::ones(videoSize, CV_8UC1);
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106
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107 boost::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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108 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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109 trajectoryDB->connect(params.databaseFilename.c_str());
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110 trajectoryDB->createTable("positions");
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111 trajectoryDB->createTable("velocities");
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112 trajectoryDB->beginTransaction();
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113
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114 vector<KeyPoint> prevKpts, currKpts;
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115 vector<Point2f> prevPts, currPts, newPts;
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116 vector<uchar> status;
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117 vector<float> errors;
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118 Mat prevDesc, currDesc;
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119
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120 vector<FeatureTrajectoryPtr> lostFeatures;
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121 vector<FeaturePointMatch> featurePointMatches;
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123 HOGDescriptor hog;
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124 hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
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126 int key = '?';
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127 unsigned int savedFeatureId=0;
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128 Mat frame, currentFrameBW, previousFrameBW;
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129
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diff changeset
130 unsigned int lastFrameNum = nFrames;
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131 if (params.nFrames >= 0)
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132 lastFrameNum = min(params.frame1+params.nFrames, nFrames);
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133
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diff changeset
134 capture.set(CV_CAP_PROP_POS_FRAMES, params.frame1);
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135 for (unsigned int frameNum = params.frame1; (frameNum < lastFrameNum) && !::interruptionKey(key); frameNum++) {
121
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diff changeset
136 capture >> frame;
227
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137 if (frameNum%50 ==0)
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138 cout << "frame " << frameNum << endl;
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139 //capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl;
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140
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diff changeset
141 // int emptyFrameNum = 0;
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142 // while (frame.empty()) {
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143 // cerr << "empty frame " << emptyFrameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES)<< endl;
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144 // capture >> frame;//break;
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145 // emptyFrameNum++;
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146 // if (emptyFrameNum>=3000)
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147 // exit(0);
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148 // }
121
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149
127
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150 cvtColor(frame, currentFrameBW, CV_RGB2GRAY);
130
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151
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152 // "normal" feature detectors: detect features here
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153 // detector.detect(currentFrameBW, currKpts); // see video_homography c++ sample
121
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154
128
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155 if (!prevPts.empty()) {
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156 //::keyPoints2Points(prevKpts, prevPts);
127
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diff changeset
157 currPts.clear();
137
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158 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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159 /// \todo try calcOpticalFlowFarneback
128
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160
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161 vector<Point2f> trackedPts;
132
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162 vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin();
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diff changeset
163 while (iter != featurePointMatches.end()) {
135
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164 bool deleteFeature = false;
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165
132
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diff changeset
166 if (status[iter->pointNum]) {
147
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diff changeset
167 iter->feature->addPoint(frameNum, currPts[iter->pointNum], homography);
135
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168
176
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169 deleteFeature |= iter->feature->isDisplacementSmall(params.nDisplacements, minTotalFeatureDisplacement)
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170 || !iter->feature->isMotionSmooth(params.accelerationBound, params.deviationBound);
139
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171 if (deleteFeature)
138
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172 iter->feature->shorten();
139
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173 } else
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174 deleteFeature = true;
135
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175
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176 if (deleteFeature) {
134
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177 if (iter->feature->length() >= params.minFeatureTime) {
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178 iter->feature->setId(savedFeatureId);
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179 savedFeatureId++;
140
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180 lostFeatures.push_back(iter->feature);
134
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181 }
132
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182 iter = featurePointMatches.erase(iter);
138
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183 } else {
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diff changeset
184 trackedPts.push_back(currPts[iter->pointNum]);
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185 iter->pointNum = trackedPts.size()-1;
135
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186 iter++;
138
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187 }
132
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188 }
128
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189 currPts = trackedPts;
132
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190 assert(currPts.size() == featurePointMatches.size());
142
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191 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities");
134
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diff changeset
192
139
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193 if (params.display) {
134
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194 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches)
147
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diff changeset
195 fp.feature->draw(frame, invHomography, Colors::red());
193
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diff changeset
196 // object detection
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197 // vector<Rect> locations;
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198 // hog.detectMultiScale(frame, locations, 0, Size(8,8), Size(32,32), 1.05, 2);
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diff changeset
199 // BOOST_FOREACH(Rect r, locations)
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diff changeset
200 // rectangle(frame, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
139
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201 }
132
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202 //drawOpticalFlow(prevPts, currPts, status, frame);
134
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203
127
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204 // cout << matches.size() << " matches" << endl;
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diff changeset
205 // descMatcher.match(currDesc, prevDesc, matches);
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diff changeset
206 // cout << matches.size() << " matches" << endl;
128
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diff changeset
207 //drawMatchesRelative(prevKpts, currKpts, matches, frame);
125
28907fde9855 work on klt tracker (problem on computer at poly)
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diff changeset
208 }
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diff changeset
209
128
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diff changeset
210 // adding new features, using mask around existing feature positions
146
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diff changeset
211 Mat featureMask = mask.clone();
128
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diff changeset
212 for (unsigned int n=0;n<currPts.size(); n++)
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diff changeset
213 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
214 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
215 featureMask.at<uchar>(i,j)=0;
130
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diff changeset
216 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.windowSize, params.useHarrisDetector, params.k);
132
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diff changeset
217 BOOST_FOREACH(Point2f p, newPts) { //for (unsigned int i=0; i<newPts.size(); i++) {
147
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diff changeset
218 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p, homography));
132
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diff changeset
219 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size()));
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diff changeset
220 currPts.push_back(p);
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diff changeset
221 }
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diff changeset
222 // currPts.insert(currPts.end(), newPts.begin(), newPts.end());
130
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diff changeset
223 //::keyPoints2Points(currKpts, currPts, false);
128
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diff changeset
224
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diff changeset
225 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location
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diff changeset
226
134
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diff changeset
227 if (params.display) {
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diff changeset
228 imshow("frame", frame);
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diff changeset
229 imshow("mask", featureMask*256);
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diff changeset
230 key = waitKey(2);
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diff changeset
231 }
127
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diff changeset
232 previousFrameBW = currentFrameBW.clone();
128
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diff changeset
233 prevPts = currPts;
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diff changeset
234 //prevKpts = currKpts;
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diff changeset
235 //currDesc.copyTo(prevDesc);
121
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diff changeset
236 }
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diff changeset
237
142
a3532db00c28 added code to write velocities
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diff changeset
238 trajectoryDB->endTransaction();
136
0f790de9437e renamed Feature to Motion files and added code to test blob db
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diff changeset
239 trajectoryDB->disconnect();
164
76610dcf3b8d added test code to read trajectories
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parents: 163
diff changeset
240 }
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diff changeset
241
169
5f705809d37a created groupFeatures function
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diff changeset
242 void groupFeatures(const KLTFeatureTrackingParameters& params) {
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diff changeset
243 boost::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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diff changeset
244 //TODO write generic methods for blob and list versions TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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diff changeset
245 bool success = trajectoryDB->connect(params.databaseFilename.c_str());
202
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parents: 194
diff changeset
246 trajectoryDB->createObjectTable("objects", "objects_features");
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parents: 194
diff changeset
247 unsigned int savedObjectId=0;
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parents: 194
diff changeset
248
188
1435965d8181 work on connected components
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diff changeset
249 // vector<boost::shared_ptr<Trajectory<Point2f> > > trajectories;
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diff changeset
250 // cout << trajectories.size() << endl;
174
ec9734015d53 tested loading trajectory by id numbers
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diff changeset
251 // std::clock_t c_start = std::clock();
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diff changeset
252 // success = trajectoryDB->read(trajectories, "positions"); // TODO load velocities as well in a FeatureTrajectory object // attention, velocities lack the first instant
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diff changeset
253 // std::clock_t c_end = std::clock();
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diff changeset
254 // cout << "Loaded " << trajectories.size() << " trajectories in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl;
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diff changeset
255
ec9734015d53 tested loading trajectory by id numbers
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diff changeset
256 // boost::shared_ptr<Trajectory<cv::Point2f> > trajectory;
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257 // c_start = std::clock();
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258 // for (unsigned int i = 0; i<trajectories.size(); ++i) {
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259 // success = trajectoryDB->read(trajectory, i, "positions");
169
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260 // }
174
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261 // c_end = std::clock();
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262 // 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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263
225
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264 trajectoryDB->createInstants("table");
221
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265
225
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266 unsigned int maxTrajectoryLength = 0;
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267 success = trajectoryDB->maxTrajectoryLength(maxTrajectoryLength);
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268 if (!success || maxTrajectoryLength == 0) {
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269 cout << "problem with trajectory length " << success << endl;
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270 exit(0);
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271 }
222
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272 cout << "Longest trajectory: " << maxTrajectoryLength << endl;
219
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273
191
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274 FeatureGraph featureGraph(params.mmConnectionDistance, params.mmSegmentationDistance, params.minFeatureTime, params.minNFeaturesPerGroup);
180
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275
169
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276 // main loop
227
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277 unsigned int frameNum;
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278 unsigned int firstFrameNum = -1, lastFrameNum = -1;
225
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279 trajectoryDB->firstLastInstants(firstFrameNum, lastFrameNum);
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280 firstFrameNum = MAX(firstFrameNum, params.frame1);
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281 if (params.nFrames>0)
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282 lastFrameNum = MIN(lastFrameNum,params.frame1+params.nFrames);
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283 for (frameNum = firstFrameNum; frameNum<lastFrameNum; frameNum ++) {
174
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284 vector<int> trajectoryIds;
180
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285 success = trajectoryDB->trajectoryIdEndingAt(trajectoryIds, frameNum); // ending
225
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286 if (frameNum%100 ==0)
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287 cout << "frame " << frameNum << endl;
222
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288 //success = trajectoryDB->trajectoryIdInInterval(trajectoryIds, frameNum, min(frameNum+queryIntervalLength-1, frameNum+params.nFrames)); // ending
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289 #if DEBUG
174
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290 cout << trajectoryIds.size() << " trajectories " << endl;
222
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291 #endif
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292 // vector<TrajectoryPoint2fPtr> positions, velocities;
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293 // trajectoryDB->read(positions, trajectoryIds, "positions");
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294 // trajectoryDB->read(velocities, trajectoryIds, "velocities");
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295 // for (unsigned int i=0; i<trajectoryIds.size(); ++i) {
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296 // FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(positions[i], velocities[i]));
174
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297 BOOST_FOREACH(int trajectoryId, trajectoryIds) {
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298 //cout << trajectoryId << " " << endl;
177
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299 // boost::shared_ptr<Trajectory<cv::Point2f> > trajectory;
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300 // success = trajectoryDB->read(trajectory, trajectoryId, "positions"); // velocities
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301 FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(trajectoryId, *trajectoryDB, "positions", "velocities"));
180
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302 // stringstream ss;ss << *ft; cout << ss.str() << endl;
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303 // cout << ft->getFirstInstant() << " " << ft->getLastInstant() << endl;
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304 featureGraph.addFeature(ft);
174
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305 }
172
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306
222
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307 // check for connected components
225
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308 int lastInstant = frameNum+params.minFeatureTime-maxTrajectoryLength;
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309 if (lastInstant > 0) {
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310 featureGraph.connectedComponents(lastInstant);
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311 vector<vector<unsigned int> > featureGroups = featureGraph.getFeatureGroups();
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312 for (unsigned int i=0; i<featureGroups.size(); ++i) {
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313 trajectoryDB->writeObject(savedObjectId, featureGroups[i], -1, 1, string("objects"), string("objects_features"));
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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);
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324 vector<vector<unsigned int> > featureGroups = featureGraph.getFeatureGroups();
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325 for (unsigned int i=0; i<featureGroups.size(); ++i) {
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326 trajectoryDB->writeObject(savedObjectId, featureGroups[i], -1, 1, string("objects"), string("objects_features"));
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327 savedObjectId++;
180
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328 }
169
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329
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330 trajectoryDB->endTransaction();
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331 trajectoryDB->disconnect();
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332 }
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333
164
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334 int main(int argc, char *argv[]) {
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335 KLTFeatureTrackingParameters params(argc, argv);
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336 cout << params.parameterDescription << endl;
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337
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338 if (params.trackFeatures)
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339 trackFeatures(params);
169
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340 else if (params.groupFeatures)
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341 groupFeatures(params);
164
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342
117
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343 return 0;
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344 }
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345
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346 /* ------------------ DOCUMENTATION ------------------ */
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347
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348
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349 /*! \mainpage
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350
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351 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are:
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352
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353 - \ref feature_based_tracking
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354
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355 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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356
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357 */
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358
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359 /*! \page feature_based_tracking Feature-based Tracking: User Manual
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360
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361 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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362
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363 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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364
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365 \section License
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366
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367 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license).
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368
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369 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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370
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371 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net.
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372
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373 */