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annotate c/feature-based-tracking.cpp @ 128:536510f60854

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new features generated as needed
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 17 Aug 2011 02:44:28 -0400
parents d19d6e63dd77
children 2a6e7a9a5c53
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1 //#include "Feature.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
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8 #include "opencv2/core/core.hpp"
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9 #include "opencv2/highgui/highgui.hpp"
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10 //#include "opencv2/imgproc/imgproc.hpp"
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11 #include "opencv2/features2d/features2d.hpp"
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12
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13 #include <boost/shared_ptr.hpp>
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15 #include <iostream>
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16 //#include <list>
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17 #include <vector>
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18
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19 using namespace std;
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20 using namespace cv;
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21 using namespace boost;
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23 void drawMatchesRelative(const vector<KeyPoint>& train, const vector<KeyPoint>& query, std::vector<cv::DMatch>& matches, Mat& img) {
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24 for (int i = 0; i < (int)matches.size(); i++)
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25 {
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26 Point2f pt_new = query[matches[i].queryIdx].pt;
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27 Point2f pt_old = train[matches[i].trainIdx].pt;
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28 Point2f dist = pt_new - pt_old;
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29 if (norm(dist) < 20) {
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30 line(img, pt_new, pt_old, Scalar(125, 255, 125), 1);
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31 circle(img, pt_old, 2, Scalar(255, 0, 125), 1);
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32 }
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33 }
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34 }
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36 void drawOpticalFlow(const vector<Point2f>& prevPts, const vector<Point2f>& currPts, const vector<uchar> status, Mat& img) {
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37 for (unsigned int i=0; i<status.size(); i++) {
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38 if (status[i]) {
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39 line(img, prevPts[i], currPts[i], Scalar(125, 255, 125), 1);
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40 circle(img, prevPts[i], 2, Scalar(255, 0, 125), 1);
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41 }
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42 }
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43 }
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45 int main(int argc, char *argv[]) {
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46 //vector<TrajectoryPoint2f> features;
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47
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48 BriefDescriptorExtractor brief(32);
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49 const int DESIRED_FTRS = 500;
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50 //shared_ptr<FeatureDetector> detector = shared_ptr<FeatureDetector>(new GridAdaptedFeatureDetector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4));
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51 //GridAdaptedFeatureDetector detector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4);
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52
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53 VideoCapture capture;
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54 Mat frame, currentFrameBW, previousFrameBW;
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55
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56 KLTFeatureTrackingParameters params;
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57 params.frame1 = 0;
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58 params.nFrames = -1;
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59 params.maxNFeatures = 1000;
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60 params.featureQuality = 0.1;
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61 params.minFeatureDistanceKLT = 3;
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62 params.windowSize = 3;
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63 params.useHarrisDetector = false;
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64 params.k = 0.4;
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65 GoodFeaturesToTrackDetector detector(params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, params.windowSize, params.useHarrisDetector, params.k);
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66
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67 params.pyramidLevel = 3;
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68 params.maxNumberTrackingIterations = 20; // 30
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69 params.minTrackingError = 0.3; // 0.01
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70 params.derivLambda = 0.5;
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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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98 // capture.open(atoi(argv[1]));
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99 if (!capture.isOpened())
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100 {
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101 //help(argv);
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102 cout << "capture device " << argv[1] << " failed to open!" << endl;
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103 return 1;
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104 }
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106 vector<KeyPoint> prevKpts, currKpts;
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107 vector<Point2f> prevPts, currPts;
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108 vector<uchar> status;
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109 vector<float> errors;
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110 Mat prevDesc, currDesc;
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113 // TODO structure de donnee paires pointeur trajectory, numero de keypoint
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114 int key = '?';
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115 for (int frameNum = params.frame1; ((params.frame1+frameNum < params.nFrames) || (params.nFrames < 0)) && !::interruptionKey(key); frameNum++) {
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116 capture >> frame;
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117 cout << capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl;
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118 while (frame.empty())
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119 capture >> frame;//break;
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120
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121 cvtColor(frame, currentFrameBW, CV_RGB2GRAY);
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123 if (!prevPts.empty()) {
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124 //::keyPoints2Points(prevKpts, prevPts);
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125 currPts.clear();
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126 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), params.derivLambda, 0); // OPTFLOW_USE_INITIAL_FLOW
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127
127
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128 drawOpticalFlow(prevPts, currPts, status, frame);
128
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129
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130 vector<Point2f> trackedPts;
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131 for (unsigned int i=0; i<status.size(); i++)
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132 if (status[i])
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133 trackedPts.push_back(currPts[i]);
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134 currPts = trackedPts;
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135
127
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136 // cout << matches.size() << " matches" << endl;
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137 // descMatcher.match(currDesc, prevDesc, matches);
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138 // cout << matches.size() << " matches" << endl;
128
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139 //drawMatchesRelative(prevKpts, currKpts, matches, frame);
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140 }
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141
128
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142 // adding new features, using mask around existing feature positions
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143 Mat featureMask = Mat::ones(videoSize, CV_8UC1);
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144 for (unsigned int n=0;n<currPts.size(); n++)
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145 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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146 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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147 featureMask.at<uchar>(i,j)=0;
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148 detector.detect(currentFrameBW, currKpts, featureMask);
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149 ::keyPoints2Points(currKpts, currPts, false);
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150
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151 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location
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152
123
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153 imshow("frame", frame);
128
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154 imshow("mask", featureMask*256);
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155 previousFrameBW = currentFrameBW.clone();
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156 prevPts = currPts;
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157 //prevKpts = currKpts;
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158 //currDesc.copyTo(prevDesc);
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159 key = waitKey(2);
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160 }
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161
117
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162 return 0;
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163 }
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164
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165
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166 /* ------------------ DOCUMENTATION ------------------ */
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167
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168
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169 /*! \mainpage
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170
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171 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are:
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172
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173 - \ref feature_based_tracking
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174
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175 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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176
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177 */
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178
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179 /*! \page feature_based_tracking Feature-based Tracking: User Manual
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180
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181 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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182
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183 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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184
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185 \section License
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186
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187 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license).
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188
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189 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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190
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191 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net.
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192
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193 */