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annotate c/feature-based-tracking.cpp @ 154:668710d4c773
updated computeTranslation with cv2
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Wed, 07 Sep 2011 16:35:51 -0400 |
parents | 0089fb29cd26 |
children | cde87a07eb58 |
rev | line source |
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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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14 |
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15 #include <boost/shared_ptr.hpp> |
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16 #include <boost/foreach.hpp> |
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17 |
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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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24 |
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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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37 |
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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 /// \todo smoothing |
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57 if (features.size() >= minNFeatures) { |
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58 BOOST_FOREACH(FeatureTrajectoryPtr f, features) f->write(db, positionsTableName, velocitiesTableName); |
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59 features.clear(); |
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60 } |
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61 } |
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62 |
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63 int main(int argc, char *argv[]) { |
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64 // BriefDescriptorExtractor brief(32); |
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65 // const int DESIRED_FTRS = 500; |
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66 // GridAdaptedFeatureDetector detector(new FastFeatureDetector(10, true), DESIRED_FTRS, 4, 4); |
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67 |
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68 VideoCapture capture; |
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69 Mat frame, currentFrameBW, previousFrameBW; |
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70 |
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71 KLTFeatureTrackingParameters params(argc, argv); |
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72 cout << params.parameterDescription << endl; |
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73 |
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74 Mat homography = ::loadMat(params.homographyFilename, " "); |
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75 Mat invHomography; |
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76 if (params.display && !homography.empty()) |
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77 invHomography = homography.inv(); |
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78 |
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79 float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement; |
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80 Size window = Size(params.windowSize, params.windowSize); |
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81 |
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82 BruteForceMatcher<Hamming> descMatcher; |
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83 vector<DMatch> matches; |
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84 Size videoSize; |
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85 |
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86 // if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) // if no parameter or number parameter |
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87 // capture.open(argc == 2 ? argv[1][0] - '0' : 0); |
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88 // else if( argc >= 2 ) |
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89 // { |
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90 // capture.open(argv[1]); |
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91 // if( capture.isOpened() ) |
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92 // videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT)); |
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93 // cout << "Video " << argv[1] << |
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94 // ": width=" << videoSize.width << |
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95 // ", height=" << videoSize.height << |
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96 // ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl; |
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97 // 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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98 // { |
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99 // sscanf(argv[2], "%d", ¶ms.frame1); |
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100 // cout << "seeking to frame #" << params.frame1 << endl; |
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101 // //cap.set(CV_CAP_PROP_POS_FRAMES, pos); |
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102 // for (int i=0; i<params.frame1; i++) |
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103 // capture >> frame; |
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104 // } |
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105 // } |
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106 |
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107 capture.open(params.videoFilename); |
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108 if(capture.isOpened()) { |
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109 videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT)); |
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110 cout << "Video " << params.videoFilename << |
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111 ": width=" << videoSize.width << |
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112 ", height=" << videoSize.height << |
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113 ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl; |
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114 } else { |
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115 cout << "Video filename " << params.videoFilename << " could not be opened. Exiting." << endl; |
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116 exit(0); |
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117 } |
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118 // if (!capture.isOpened()) |
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119 // { |
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120 // //help(argv); |
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121 // cout << "capture device " << argv[1] << " failed to open!" << endl; |
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122 // return 1; |
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123 // } |
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124 |
146
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125 Mat mask = imread(params.maskFilename, 0); |
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126 if (mask.empty()) |
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127 mask = Mat::ones(videoSize, CV_8UC1); |
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128 |
140
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129 boost::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>()); |
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130 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>(); |
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131 trajectoryDB->connect(params.databaseFilename.c_str()); |
142
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132 trajectoryDB->createTable("positions"); |
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133 trajectoryDB->createTable("velocities"); |
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134 trajectoryDB->beginTransaction(); |
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135 |
124
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136 vector<KeyPoint> prevKpts, currKpts; |
130
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137 vector<Point2f> prevPts, currPts, newPts; |
127
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138 vector<uchar> status; |
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139 vector<float> errors; |
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140 Mat prevDesc, currDesc; |
128
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141 |
140
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142 vector<FeatureTrajectoryPtr> lostFeatures; |
132
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143 vector<FeaturePointMatch> featurePointMatches; |
130
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144 |
133
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145 int key = '?'; |
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146 unsigned int savedFeatureId=0; |
141
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147 for (int frameNum = params.frame1; ((frameNum-params.frame1 < params.nFrames) || (params.nFrames < 0)) && !::interruptionKey(key); frameNum++) { |
121
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148 capture >> frame; |
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149 cout << frameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl; |
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150 int emptyFrameNum = 0; |
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151 while (frame.empty()) { |
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152 cerr << "empty frame " << emptyFrameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES)<< endl; |
123
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153 capture >> frame;//break; |
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154 emptyFrameNum++; |
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155 if (emptyFrameNum>=3000) |
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156 exit(0); |
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157 } |
121
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158 |
127
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159 cvtColor(frame, currentFrameBW, CV_RGB2GRAY); |
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160 |
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161 // "normal" feature detectors: detect features here |
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162 // detector.detect(currentFrameBW, currKpts); // see video_homography c++ sample |
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163 |
128
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164 if (!prevPts.empty()) { |
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165 //::keyPoints2Points(prevKpts, prevPts); |
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166 currPts.clear(); |
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167 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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168 /// \todo try calcOpticalFlowFarneback |
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169 |
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170 vector<Point2f> trackedPts; |
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171 vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin(); |
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172 while (iter != featurePointMatches.end()) { |
135
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173 bool deleteFeature = false; |
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174 |
132
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175 if (status[iter->pointNum]) { |
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176 iter->feature->addPoint(frameNum, currPts[iter->pointNum], homography); |
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177 |
139
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178 deleteFeature |= iter->feature->smallDisplacement(params.nDisplacements, minTotalFeatureDisplacement) |
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179 || !iter->feature->motionSmooth(params.accelerationBound, params.deviationBound); |
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180 if (deleteFeature) |
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181 iter->feature->shorten(); |
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182 } else |
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183 deleteFeature = true; |
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184 |
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185 if (deleteFeature) { |
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186 if (iter->feature->length() >= params.minFeatureTime) { |
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187 iter->feature->setId(savedFeatureId); |
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188 savedFeatureId++; |
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189 lostFeatures.push_back(iter->feature); |
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190 } |
132
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191 iter = featurePointMatches.erase(iter); |
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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; |
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195 iter++; |
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196 } |
132
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197 } |
128
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198 currPts = trackedPts; |
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199 assert(currPts.size() == featurePointMatches.size()); |
142
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200 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities"); |
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201 |
139
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202 if (params.display) { |
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203 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches) |
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204 fp.feature->draw(frame, invHomography, Colors::red()); |
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205 } |
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206 //drawOpticalFlow(prevPts, currPts, status, frame); |
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207 |
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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; |
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211 //drawMatchesRelative(prevKpts, currKpts, matches, frame); |
125
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212 } |
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213 |
128
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214 // adding new features, using mask around existing feature positions |
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215 Mat featureMask = mask.clone(); |
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216 for (unsigned int n=0;n<currPts.size(); n++) |
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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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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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219 featureMask.at<uchar>(i,j)=0; |
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220 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.windowSize, params.useHarrisDetector, params.k); |
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221 BOOST_FOREACH(Point2f p, newPts) { //for (unsigned int i=0; i<newPts.size(); i++) { |
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222 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p, homography)); |
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223 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size())); |
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224 currPts.push_back(p); |
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225 } |
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226 // currPts.insert(currPts.end(), newPts.begin(), newPts.end()); |
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227 //::keyPoints2Points(currKpts, currPts, false); |
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228 |
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229 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location |
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230 |
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231 if (params.display) { |
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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 } |
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236 previousFrameBW = currentFrameBW.clone(); |
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237 prevPts = currPts; |
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238 //prevKpts = currKpts; |
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239 //currDesc.copyTo(prevDesc); |
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240 } |
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241 |
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242 trajectoryDB->endTransaction(); |
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243 trajectoryDB->disconnect(); |
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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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248 /* ------------------ DOCUMENTATION ------------------ */ |
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249 |
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250 |
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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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256 |
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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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260 |
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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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272 |
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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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274 |
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275 */ |