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annotate c/feature-based-tracking.cpp @ 146:7150427c665e

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added loading of mask
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 30 Aug 2011 13:04:36 -0400
parents 7bf8084e720f
children 0089fb29cd26
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1 #include "Motion.hpp"
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2 #include "Parameters.hpp"
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3 #include "cvutils.hpp"
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4 #include "utils.hpp"
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5
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6 #include "src/Trajectory.h"
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7 #include "src/TrajectoryDBAccessList.h"
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8 #include "src/TrajectoryDBAccessBlob.h"
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9
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10 #include "opencv2/core/core.hpp"
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11 #include "opencv2/highgui/highgui.hpp"
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12 //#include "opencv2/imgproc/imgproc.hpp"
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13 #include "opencv2/features2d/features2d.hpp"
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15 #include <boost/shared_ptr.hpp>
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16 #include <boost/foreach.hpp>
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18 #include <iostream>
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19 //#include <list>
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20 #include <vector>
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21
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22 using namespace std;
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23 using namespace cv;
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25 void drawMatchesRelative(const vector<KeyPoint>& train, const vector<KeyPoint>& query, std::vector<cv::DMatch>& matches, Mat& img) {
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26 for (int i = 0; i < (int)matches.size(); i++)
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27 {
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28 Point2f pt_new = query[matches[i].queryIdx].pt;
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29 Point2f pt_old = train[matches[i].trainIdx].pt;
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30 Point2f dist = pt_new - pt_old;
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31 if (norm(dist) < 20) {
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32 line(img, pt_new, pt_old, Scalar(125, 255, 125), 1);
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33 circle(img, pt_old, 2, Scalar(255, 0, 125), 1);
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34 }
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35 }
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36 }
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38 void drawOpticalFlow(const vector<Point2f>& prevPts, const vector<Point2f>& currPts, const vector<uchar> status, Mat& img) {
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39 for (unsigned int i=0; i<status.size(); i++) {
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40 if (status[i]) {
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41 line(img, prevPts[i], currPts[i], Scalar(125, 255, 125), 1);
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42 circle(img, prevPts[i], 2, Scalar(255, 0, 125), 1);
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43 }
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44 }
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45 }
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46
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47 struct FeaturePointMatch {
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48 FeatureTrajectoryPtr feature;
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49 int pointNum;
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50
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51 FeaturePointMatch(FeatureTrajectoryPtr _feature, const int& _pointNum):
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52 feature(_feature), pointNum(_pointNum) {}
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53 };
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54
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55 inline void saveFeatures(vector<FeatureTrajectoryPtr>& features, TrajectoryDBAccess<Point2f>& db, const string& positionsTableName, const string& velocitiesTableName, const unsigned int& minNFeatures = 0) {
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56 if (features.size() >= minNFeatures) {
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57 BOOST_FOREACH(FeatureTrajectoryPtr f, features) f->write(db, positionsTableName, velocitiesTableName);
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58 features.clear();
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59 }
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60 }
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62 int main(int argc, char *argv[]) {
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63 // BriefDescriptorExtractor brief(32);
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64 // const int DESIRED_FTRS = 500;
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65 // GridAdaptedFeatureDetector detector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4);
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67 VideoCapture capture;
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68 Mat frame, currentFrameBW, previousFrameBW;
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69
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70 KLTFeatureTrackingParameters params(argc, argv);
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71 cout << params.parameterDescription << endl;
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72
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73 Mat m = ::loadMat(params.homographyFilename, " ");
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74 //cout << m << endl;
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76 float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement;
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77 Size window = Size(params.windowSize, params.windowSize);
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78
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79 BruteForceMatcher<Hamming> descMatcher;
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80 vector<DMatch> matches;
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81 Size videoSize;
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83 // if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) // if no parameter or number parameter
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84 // capture.open(argc == 2 ? argv[1][0] - '0' : 0);
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85 // else if( argc >= 2 )
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86 // {
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87 // capture.open(argv[1]);
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88 // if( capture.isOpened() )
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89 // videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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90 // cout << "Video " << argv[1] <<
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91 // ": width=" << videoSize.width <<
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92 // ", height=" << videoSize.height <<
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93 // ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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94 // 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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95 // {
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96 // sscanf(argv[2], "%d", &params.frame1);
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97 // cout << "seeking to frame #" << params.frame1 << endl;
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98 // //cap.set(CV_CAP_PROP_POS_FRAMES, pos);
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99 // for (int i=0; i<params.frame1; i++)
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100 // capture >> frame;
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101 // }
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102 // }
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104 capture.open(params.videoFilename);
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105 if(capture.isOpened()) {
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106 videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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107 cout << "Video " << params.videoFilename <<
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108 ": width=" << videoSize.width <<
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109 ", height=" << videoSize.height <<
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110 ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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111 } else {
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112 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl;
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113 exit(0);
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114 }
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115 // if (!capture.isOpened())
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116 // {
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117 // //help(argv);
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118 // cout << "capture device " << argv[1] << " failed to open!" << endl;
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119 // return 1;
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120 // }
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121
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122 // mask
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123 Mat mask = imread(params.maskFilename, 0);
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124 if (mask.empty())
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125 mask = Mat::ones(videoSize, CV_8UC1);
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127 // database
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128 boost::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>());
136
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129 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
138
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130 trajectoryDB->connect(params.databaseFilename.c_str());
142
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131 trajectoryDB->createTable("positions");
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132 trajectoryDB->createTable("velocities");
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133 trajectoryDB->beginTransaction();
133
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134
124
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diff changeset
135 vector<KeyPoint> prevKpts, currKpts;
130
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136 vector<Point2f> prevPts, currPts, newPts;
127
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137 vector<uchar> status;
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138 vector<float> errors;
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139 Mat prevDesc, currDesc;
128
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140
140
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141 vector<FeatureTrajectoryPtr> lostFeatures;
132
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142 vector<FeaturePointMatch> featurePointMatches;
130
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143
133
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144 int key = '?';
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145 unsigned int savedFeatureId=0;
141
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146 for (int frameNum = params.frame1; ((frameNum-params.frame1 < params.nFrames) || (params.nFrames < 0)) && !::interruptionKey(key); frameNum++) {
121
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147 capture >> frame;
134
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148 cout << frameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl;
145
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149 int emptyFrameNum = 0;
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150 while (frame.empty()) {
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151 cerr << "empty frame " << emptyFrameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES)<< endl;
123
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152 capture >> frame;//break;
145
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153 emptyFrameNum++;
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154 if (emptyFrameNum>=3000)
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155 exit(0);
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156 }
121
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157
127
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158 cvtColor(frame, currentFrameBW, CV_RGB2GRAY);
130
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159
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160 // "normal" feature detectors: detect features here
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161 // detector.detect(currentFrameBW, currKpts); // see video_homography c++ sample
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162
128
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163 if (!prevPts.empty()) {
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164 //::keyPoints2Points(prevKpts, prevPts);
127
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165 currPts.clear();
137
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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
128
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167
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168 vector<Point2f> trackedPts;
132
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169 vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin();
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170 while (iter != featurePointMatches.end()) {
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171 bool deleteFeature = false;
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172
132
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173 if (status[iter->pointNum]) {
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174 iter->feature->addPoint(frameNum, currPts[iter->pointNum]);
135
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175
139
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176 deleteFeature |= iter->feature->smallDisplacement(params.nDisplacements, minTotalFeatureDisplacement)
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177 || !iter->feature->motionSmooth(params.accelerationBound, params.deviationBound);
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178 if (deleteFeature)
138
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179 iter->feature->shorten();
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180 } else
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181 deleteFeature = true;
135
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182
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183 if (deleteFeature) {
134
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184 if (iter->feature->length() >= params.minFeatureTime) {
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185 iter->feature->setId(savedFeatureId);
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186 savedFeatureId++;
139
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187 /// \todo smoothing
140
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188 //iter->feature->write(*trajectoryDB);
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189 lostFeatures.push_back(iter->feature);
134
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190 }
132
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191 iter = featurePointMatches.erase(iter);
138
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192 } else {
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193 trackedPts.push_back(currPts[iter->pointNum]);
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194 iter->pointNum = trackedPts.size()-1;
135
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diff changeset
195 iter++;
138
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196 }
132
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197 }
128
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198 currPts = trackedPts;
132
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199 assert(currPts.size() == featurePointMatches.size());
142
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200 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities");
134
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diff changeset
201
139
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diff changeset
202 if (params.display) {
134
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203 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches)
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204 fp.feature->draw(frame, Colors::red());
139
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205 }
132
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206 //drawOpticalFlow(prevPts, currPts, status, frame);
134
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diff changeset
207
127
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208 // cout << matches.size() << " matches" << endl;
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209 // descMatcher.match(currDesc, prevDesc, matches);
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210 // cout << matches.size() << " matches" << endl;
128
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211 //drawMatchesRelative(prevKpts, currKpts, matches, frame);
125
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diff changeset
212 }
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diff changeset
213
128
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diff changeset
214 // adding new features, using mask around existing feature positions
146
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diff changeset
215 Mat featureMask = mask.clone();
128
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diff changeset
216 for (unsigned int n=0;n<currPts.size(); n++)
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diff changeset
217 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
218 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
219 featureMask.at<uchar>(i,j)=0;
130
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diff changeset
220 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.windowSize, params.useHarrisDetector, params.k);
132
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diff changeset
221 BOOST_FOREACH(Point2f p, newPts) { //for (unsigned int i=0; i<newPts.size(); i++) {
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diff changeset
222 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p));
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diff changeset
223 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size()));
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diff changeset
224 currPts.push_back(p);
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225 }
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diff changeset
226 // currPts.insert(currPts.end(), newPts.begin(), newPts.end());
130
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diff changeset
227 //::keyPoints2Points(currKpts, currPts, false);
128
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diff changeset
228
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diff changeset
229 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location
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diff changeset
230
134
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diff changeset
231 if (params.display) {
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diff changeset
232 imshow("frame", frame);
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233 imshow("mask", featureMask*256);
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234 key = waitKey(2);
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235 }
127
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diff changeset
236 previousFrameBW = currentFrameBW.clone();
128
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diff changeset
237 prevPts = currPts;
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238 //prevKpts = currKpts;
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diff changeset
239 //currDesc.copyTo(prevDesc);
121
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diff changeset
240 }
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diff changeset
241
142
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diff changeset
242 trajectoryDB->endTransaction();
136
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diff changeset
243 trajectoryDB->disconnect();
117
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244 return 0;
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245 }
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246
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247
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diff changeset
248 /* ------------------ DOCUMENTATION ------------------ */
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249
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250
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diff changeset
251 /*! \mainpage
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252
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253 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are:
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254
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255 - \ref feature_based_tracking
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257 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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258
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259 */
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261 /*! \page feature_based_tracking Feature-based Tracking: User Manual
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262
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263 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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264
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265 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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266
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267 \section License
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268
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269 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license).
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270
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271 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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273 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net.
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275 */