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annotate c/feature-based-tracking.cpp @ 225:d4d3b1e8a9f1

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added code to process only needed frames based on saved features
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 26 Jun 2012 03:37:19 -0400
parents 426321b46e44
children b7612c6d5702
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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1 #include "Motion.hpp"
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2 #include "Parameters.hpp"
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3 #include "cvutils.hpp"
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4 #include "utils.hpp"
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5
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6 #include "src/Trajectory.h"
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7 #include "src/TrajectoryDBAccessList.h"
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8 #include "src/TrajectoryDBAccessBlob.h"
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10 #include "opencv2/core/core.hpp"
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11 #include "opencv2/imgproc/imgproc.hpp"
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12 #include "opencv2/video/tracking.hpp"
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13 #include "opencv2/features2d/features2d.hpp"
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14 #include "opencv2/highgui/highgui.hpp"
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15 #include "opencv2/objdetect/objdetect.hpp"
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16
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17 #include <boost/shared_ptr.hpp>
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18 #include <boost/foreach.hpp>
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19
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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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23
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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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48
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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 Size videoSize;
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81
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82 // if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) // if no parameter or number parameter
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83 // capture.open(argc == 2 ? argv[1][0] - '0' : 0);
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84 // else if( argc >= 2 )
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85 // {
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86 // capture.open(argv[1]);
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87 // if( capture.isOpened() )
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88 // videoSize = Size(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT));
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89 // cout << "Video " << argv[1] <<
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90 // ": width=" << videoSize.width <<
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91 // ", height=" << videoSize.height <<
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92 // ", nframes=" << capture.get(CV_CAP_PROP_FRAME_COUNT) << endl;
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93 // 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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94 // {
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95 // sscanf(argv[2], "%d", &params.frame1);
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96 // cout << "seeking to frame #" << params.frame1 << endl;
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97 // //cap.set(CV_CAP_PROP_POS_FRAMES, pos);
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98 // for (int i=0; i<params.frame1; i++)
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99 // capture >> frame;
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100 // }
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101 // }
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102
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103 VideoCapture capture;
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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 Mat mask = imread(params.maskFilename, 0);
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123 if (mask.empty())
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124 mask = Mat::ones(videoSize, CV_8UC1);
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125
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126 boost::shared_ptr<TrajectoryDBAccess<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccess<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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127 //TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
138
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diff changeset
128 trajectoryDB->connect(params.databaseFilename.c_str());
142
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diff changeset
129 trajectoryDB->createTable("positions");
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diff changeset
130 trajectoryDB->createTable("velocities");
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parents: 141
diff changeset
131 trajectoryDB->beginTransaction();
133
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diff changeset
132
124
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diff changeset
133 vector<KeyPoint> prevKpts, currKpts;
130
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diff changeset
134 vector<Point2f> prevPts, currPts, newPts;
127
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diff changeset
135 vector<uchar> status;
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diff changeset
136 vector<float> errors;
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diff changeset
137 Mat prevDesc, currDesc;
128
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diff changeset
138
140
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diff changeset
139 vector<FeatureTrajectoryPtr> lostFeatures;
132
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diff changeset
140 vector<FeaturePointMatch> featurePointMatches;
163
cde87a07eb58 added graph structures
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diff changeset
141
193
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142 HOGDescriptor hog;
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143 hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
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144
133
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145 int key = '?';
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146 unsigned int savedFeatureId=0;
164
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diff changeset
147 Mat frame, currentFrameBW, previousFrameBW;
141
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148 for (int frameNum = params.frame1; ((frameNum-params.frame1 < params.nFrames) || (params.nFrames < 0)) && !::interruptionKey(key); frameNum++) {
121
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diff changeset
149 capture >> frame;
134
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150 cout << frameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES) << " " << prevPts.size() << endl;
145
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diff changeset
151 int emptyFrameNum = 0;
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diff changeset
152 while (frame.empty()) {
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153 cerr << "empty frame " << emptyFrameNum << " " << capture.get(CV_CAP_PROP_POS_FRAMES)<< endl;
123
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diff changeset
154 capture >> frame;//break;
145
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diff changeset
155 emptyFrameNum++;
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diff changeset
156 if (emptyFrameNum>=3000)
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diff changeset
157 exit(0);
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diff changeset
158 }
121
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diff changeset
159
127
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diff changeset
160 cvtColor(frame, currentFrameBW, CV_RGB2GRAY);
130
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161
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diff changeset
162 // "normal" feature detectors: detect features here
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163 // detector.detect(currentFrameBW, currKpts); // see video_homography c++ sample
121
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164
128
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165 if (!prevPts.empty()) {
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166 //::keyPoints2Points(prevKpts, prevPts);
127
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diff changeset
167 currPts.clear();
137
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diff changeset
168 calcOpticalFlowPyrLK(previousFrameBW, currentFrameBW, prevPts, currPts, status, errors, window, params.pyramidLevel, TermCriteria(3 /*static_cast<int>(TermCriteria::COUNT)+static_cast<int>(TermCriteria::EPS)*/, params.maxNumberTrackingIterations, params.minTrackingError), 0.5 /* unused */, 0); // OPTFLOW_USE_INITIAL_FLOW
154
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diff changeset
169 /// \todo try calcOpticalFlowFarneback
128
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170
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diff changeset
171 vector<Point2f> trackedPts;
132
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diff changeset
172 vector<FeaturePointMatch>::iterator iter = featurePointMatches.begin();
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diff changeset
173 while (iter != featurePointMatches.end()) {
135
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diff changeset
174 bool deleteFeature = false;
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175
132
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diff changeset
176 if (status[iter->pointNum]) {
147
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diff changeset
177 iter->feature->addPoint(frameNum, currPts[iter->pointNum], homography);
135
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diff changeset
178
176
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diff changeset
179 deleteFeature |= iter->feature->isDisplacementSmall(params.nDisplacements, minTotalFeatureDisplacement)
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180 || !iter->feature->isMotionSmooth(params.accelerationBound, params.deviationBound);
139
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diff changeset
181 if (deleteFeature)
138
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diff changeset
182 iter->feature->shorten();
139
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diff changeset
183 } else
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diff changeset
184 deleteFeature = true;
135
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diff changeset
185
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diff changeset
186 if (deleteFeature) {
134
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diff changeset
187 if (iter->feature->length() >= params.minFeatureTime) {
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diff changeset
188 iter->feature->setId(savedFeatureId);
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diff changeset
189 savedFeatureId++;
140
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diff changeset
190 lostFeatures.push_back(iter->feature);
134
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191 }
132
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diff changeset
192 iter = featurePointMatches.erase(iter);
138
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diff changeset
193 } else {
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diff changeset
194 trackedPts.push_back(currPts[iter->pointNum]);
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diff changeset
195 iter->pointNum = trackedPts.size()-1;
135
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diff changeset
196 iter++;
138
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197 }
132
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198 }
128
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diff changeset
199 currPts = trackedPts;
132
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diff changeset
200 assert(currPts.size() == featurePointMatches.size());
142
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diff changeset
201 saveFeatures(lostFeatures, *trajectoryDB, "positions", "velocities");
134
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diff changeset
202
139
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diff changeset
203 if (params.display) {
134
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diff changeset
204 BOOST_FOREACH(FeaturePointMatch fp, featurePointMatches)
147
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diff changeset
205 fp.feature->draw(frame, invHomography, Colors::red());
193
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diff changeset
206 // object detection
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diff changeset
207 // vector<Rect> locations;
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diff changeset
208 // hog.detectMultiScale(frame, locations, 0, Size(8,8), Size(32,32), 1.05, 2);
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diff changeset
209 // BOOST_FOREACH(Rect r, locations)
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diff changeset
210 // rectangle(frame, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
139
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diff changeset
211 }
132
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diff changeset
212 //drawOpticalFlow(prevPts, currPts, status, frame);
134
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diff changeset
213
127
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diff changeset
214 // cout << matches.size() << " matches" << endl;
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diff changeset
215 // descMatcher.match(currDesc, prevDesc, matches);
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diff changeset
216 // cout << matches.size() << " matches" << endl;
128
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diff changeset
217 //drawMatchesRelative(prevKpts, currKpts, matches, frame);
125
28907fde9855 work on klt tracker (problem on computer at poly)
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parents: 124
diff changeset
218 }
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diff changeset
219
128
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diff changeset
220 // adding new features, using mask around existing feature positions
146
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diff changeset
221 Mat featureMask = mask.clone();
128
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diff changeset
222 for (unsigned int n=0;n<currPts.size(); n++)
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diff changeset
223 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
224 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
225 featureMask.at<uchar>(i,j)=0;
130
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diff changeset
226 goodFeaturesToTrack(currentFrameBW, newPts, params.maxNFeatures, params.featureQuality, params.minFeatureDistanceKLT, featureMask, params.windowSize, params.useHarrisDetector, params.k);
132
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diff changeset
227 BOOST_FOREACH(Point2f p, newPts) { //for (unsigned int i=0; i<newPts.size(); i++) {
147
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diff changeset
228 FeatureTrajectoryPtr f = FeatureTrajectoryPtr(new FeatureTrajectory(frameNum, p, homography));
132
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diff changeset
229 featurePointMatches.push_back(FeaturePointMatch(f, currPts.size()));
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diff changeset
230 currPts.push_back(p);
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diff changeset
231 }
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diff changeset
232 // currPts.insert(currPts.end(), newPts.begin(), newPts.end());
130
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diff changeset
233 //::keyPoints2Points(currKpts, currPts, false);
128
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diff changeset
234
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diff changeset
235 //brief.compute(currentFrameBW, currKpts, currDesc); //Compute brief descriptors at each keypoint location
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diff changeset
236
134
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diff changeset
237 if (params.display) {
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diff changeset
238 imshow("frame", frame);
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diff changeset
239 imshow("mask", featureMask*256);
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diff changeset
240 key = waitKey(2);
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diff changeset
241 }
127
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diff changeset
242 previousFrameBW = currentFrameBW.clone();
128
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diff changeset
243 prevPts = currPts;
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diff changeset
244 //prevKpts = currKpts;
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diff changeset
245 //currDesc.copyTo(prevDesc);
121
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diff changeset
246 }
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diff changeset
247
142
a3532db00c28 added code to write velocities
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diff changeset
248 trajectoryDB->endTransaction();
136
0f790de9437e renamed Feature to Motion files and added code to test blob db
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diff changeset
249 trajectoryDB->disconnect();
164
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parents: 163
diff changeset
250 }
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parents: 163
diff changeset
251
169
5f705809d37a created groupFeatures function
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parents: 168
diff changeset
252 void groupFeatures(const KLTFeatureTrackingParameters& params) {
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253 boost::shared_ptr<TrajectoryDBAccessList<Point2f> > trajectoryDB = boost::shared_ptr<TrajectoryDBAccessList<Point2f> >(new TrajectoryDBAccessList<Point2f>());
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254 //TODO write generic methods for blob and list versions TrajectoryDBAccess<Point2f>* trajectoryDB = new TrajectoryDBAccessBlob<Point2f>();
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255 bool success = trajectoryDB->connect(params.databaseFilename.c_str());
202
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256 trajectoryDB->createObjectTable("objects", "objects_features");
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257 unsigned int savedObjectId=0;
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258
188
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259 // vector<boost::shared_ptr<Trajectory<Point2f> > > trajectories;
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260 // cout << trajectories.size() << endl;
174
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261 // std::clock_t c_start = std::clock();
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262 // success = trajectoryDB->read(trajectories, "positions"); // TODO load velocities as well in a FeatureTrajectory object // attention, velocities lack the first instant
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263 // std::clock_t c_end = std::clock();
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264 // cout << "Loaded " << trajectories.size() << " trajectories in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl;
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265
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266 // boost::shared_ptr<Trajectory<cv::Point2f> > trajectory;
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267 // c_start = std::clock();
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268 // for (unsigned int i = 0; i<trajectories.size(); ++i) {
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269 // success = trajectoryDB->read(trajectory, i, "positions");
169
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270 // }
174
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271 // c_end = std::clock();
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272 // cout << "Loaded " << trajectories.size() << " trajectories one by one in " << 1000.0 * (c_end-c_start) / CLOCKS_PER_SEC << " CPU seconds" << endl;
169
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273
225
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274 trajectoryDB->createInstants("table");
221
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275
225
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276 unsigned int maxTrajectoryLength = 0;
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277 success = trajectoryDB->maxTrajectoryLength(maxTrajectoryLength);
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278 if (!success || maxTrajectoryLength == 0) {
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279 cout << "problem with trajectory length " << success << endl;
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280 exit(0);
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281 }
222
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282 cout << "Longest trajectory: " << maxTrajectoryLength << endl;
219
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283
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284 // alternative: read and load features in batches directly select * from positions where trajectory_id in select trajectory_id from positions where frame_number <100 and frame_number > 50 group by trajectory_id
222
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285 int queryIntervalLength = 10;
169
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286
191
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287 FeatureGraph featureGraph(params.mmConnectionDistance, params.mmSegmentationDistance, params.minFeatureTime, params.minNFeaturesPerGroup);
180
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288
169
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289 // main loop
225
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290 int frameNum;
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291 unsigned int firstFrameNum, lastFrameNum;
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292 trajectoryDB->firstLastInstants(firstFrameNum, lastFrameNum);
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293 firstFrameNum = MAX(firstFrameNum, params.frame1);
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294 if (params.nFrames>0)
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295 lastFrameNum = MIN(lastFrameNum,params.frame1+params.nFrames);
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296 for (frameNum = firstFrameNum; frameNum<lastFrameNum; frameNum ++) {
174
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297 vector<int> trajectoryIds;
180
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298 success = trajectoryDB->trajectoryIdEndingAt(trajectoryIds, frameNum); // ending
225
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299 if (frameNum%100 ==0)
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300 cout << "frame " << frameNum << endl;
222
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301 //success = trajectoryDB->trajectoryIdInInterval(trajectoryIds, frameNum, min(frameNum+queryIntervalLength-1, frameNum+params.nFrames)); // ending
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302 #if DEBUG
174
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303 cout << trajectoryIds.size() << " trajectories " << endl;
222
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304 #endif
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305 // vector<TrajectoryPoint2fPtr> positions, velocities;
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306 // trajectoryDB->read(positions, trajectoryIds, "positions");
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307 // trajectoryDB->read(velocities, trajectoryIds, "velocities");
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308 // for (unsigned int i=0; i<trajectoryIds.size(); ++i) {
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309 // FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(positions[i], velocities[i]));
174
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310 BOOST_FOREACH(int trajectoryId, trajectoryIds) {
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311 //cout << trajectoryId << " " << endl;
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312 // boost::shared_ptr<Trajectory<cv::Point2f> > trajectory;
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313 // success = trajectoryDB->read(trajectory, trajectoryId, "positions"); // velocities
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314 FeatureTrajectoryPtr ft = FeatureTrajectoryPtr(new FeatureTrajectory(trajectoryId, *trajectoryDB, "positions", "velocities"));
180
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315 // stringstream ss;ss << *ft; cout << ss.str() << endl;
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316 // cout << ft->getFirstInstant() << " " << ft->getLastInstant() << endl;
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317 featureGraph.addFeature(ft);
174
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318 }
172
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319
222
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320 // check for connected components
225
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321 int lastInstant = frameNum+params.minFeatureTime-maxTrajectoryLength;
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322 if (lastInstant > 0) {
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323 featureGraph.connectedComponents(lastInstant);
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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++;
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328 }
188
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329 }
222
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330
225
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331 if (frameNum%100 ==0)
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332 cout << featureGraph.informationString() << endl;
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333 }
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334
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335 // save remaining objects
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336 featureGraph.connectedComponents(frameNum+maxTrajectoryLength+1);
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337 vector<vector<unsigned int> > featureGroups = featureGraph.getFeatureGroups();
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338 for (unsigned int i=0; i<featureGroups.size(); ++i) {
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339 trajectoryDB->writeObject(savedObjectId, featureGroups[i], -1, 1, string("objects"), string("objects_features"));
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340 savedObjectId++;
180
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341 }
169
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342
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343 trajectoryDB->endTransaction();
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344 trajectoryDB->disconnect();
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345 }
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346
164
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347 int main(int argc, char *argv[]) {
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348 KLTFeatureTrackingParameters params(argc, argv);
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349 cout << params.parameterDescription << endl;
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350
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351 if (params.trackFeatures)
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352 trackFeatures(params);
169
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353 else if (params.groupFeatures)
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354 groupFeatures(params);
164
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355
117
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356 return 0;
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357 }
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358
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359 /* ------------------ DOCUMENTATION ------------------ */
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360
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361
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362 /*! \mainpage
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363
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364 This project is a collection of software tools for transportation called Traffic Intelligence. Other documents are:
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365
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366 - \ref feature_based_tracking
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367
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368 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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369
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370 */
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371
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372 /*! \page feature_based_tracking Feature-based Tracking: User Manual
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373
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374 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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375
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376 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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377
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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378 \section License
fea680fb03ee created main feature based tracking file and minimum doxygen documentation
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379
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380 The code is licensed under the MIT open source license (http://www.opensource.org/licenses/mit-license).
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381
fea680fb03ee created main feature based tracking file and minimum doxygen documentation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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382 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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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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383
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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384 Contact me at nicolas.saunier@polymtl.ca and learn more about my work at http://nicolas.saunier.confins.net.
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fea680fb03ee created main feature based tracking file and minimum doxygen documentation
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386 */