Mercurial Hosting > traffic-intelligence
annotate tracking.cfg @ 788:5b970a5bc233 dev
updated classifying code to OpenCV 3.x (bug in function to load classification models)
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Thu, 24 Mar 2016 16:37:37 -0400 |
parents | 56153d439f8c |
children | f7cf43b5ad3b 21f10332c72b |
rev | line source |
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1 # filename of the video to process |
319 | 2 video-filename = laurier.avi |
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3 # filename of the database where results are saved |
319 | 4 database-filename = laurier.sqlite |
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5 # filename of the homography matrix |
319 | 6 homography-filename = laurier-homography.txt |
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7 # filename of the camera intrinsic matrix |
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8 intrinsic-camera-filename = intrinsic-camera.txt |
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9 # -0.11759321 0.0148536 0.00030756 -0.00020578 -0.00091816 |
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10 distortion-coefficients = -0.11759321 |
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11 distortion-coefficients = 0.0148536 |
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12 distortion-coefficients = 0.00030756 |
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13 distortion-coefficients = -0.00020578 |
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14 distortion-coefficients = -0.00091816 |
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15 # undistorted image multiplication |
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16 undistorted-size-multiplication = 1.31 |
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17 # Interpolation method for remapping image when correcting for distortion: 0 for INTER_NEAREST - a nearest-neighbor interpolation; 1 for INTER_LINEAR - a bilinear interpolation (used by default); 2 for INTER_CUBIC - a bicubic interpolation over 4x4 pixel neighborhood; 3 for INTER_LANCZOS4 |
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18 interpolation-method = 1 |
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19 # filename of the mask image (where features are detected) |
319 | 20 mask-filename = none |
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21 # undistort the video for feature tracking |
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22 undistort = false |
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23 # load features from database |
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24 load-features = false |
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25 # display trajectories on the video |
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26 display = false |
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27 # original video frame rate (number of frames/s) |
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28 video-fps = 29.97 |
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29 # number of digits of precision for all measurements derived from video |
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30 # measurement-precision = 3 |
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31 # first frame to process |
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32 frame1 = 0 |
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33 # number of frame to process: 0 means processing all frames |
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34 nframes = 0 |
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35 # feature tracking |
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36 # maximum number of features added at each frame |
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37 max-nfeatures = 1000 |
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38 # quality level of the good features to track |
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39 feature-quality = 0.0812219538558 |
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40 # minimum distance between features (px) |
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41 min-feature-distanceklt = 3.54964337411 |
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42 # size of the block for feature characteristics (px) |
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43 block-size = 7 |
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44 # use of Harris corner detector |
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45 use-harris-detector = false |
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46 # k parameter to detect good features to track (OpenCV) |
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47 k = 0.4 |
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48 # size of the search window at each pyramid level (px) |
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49 window-size = 6 |
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50 # maximal pyramid level in the feature tracking algorithm |
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51 pyramid-level = 5 |
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52 # number of displacement to test minimum feature motion |
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53 ndisplacements = 3 |
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54 # minimum displacement to keep features (px) |
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55 min-feature-displacement = 0.05 |
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56 # maximum feature acceleration |
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57 acceleration-bound = 3 |
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58 # maximum feature deviation |
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59 deviation-bound = 0.6 |
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60 # number of frames to smooth positions (half window) |
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61 smoothing-halfwidth = 5 |
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62 # number of frames to compute velocities |
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63 #nframes-velocity = 5 |
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64 # maximum number of iterations to stop feature tracking |
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65 max-number-iterations = 20 |
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66 # minimum error to reach to stop feature tracking |
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67 min-tracking-error = 0.183328975142 |
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68 # minimum eigen value of a 2x2 normal matrix of optical flow equations |
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69 min-feature-eig-threshold = 1e-4 |
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70 # minimum length of a feature (number of frames) to consider a feature for grouping |
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71 min-feature-time = 9 |
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72 # Min Max similarity parameters (Beymer et al. method) |
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73 # connection distance in feature grouping (world distance unit or px) |
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74 mm-connection-distance = 2.68813545522 |
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75 # segmentation distance in feature grouping (world distance unit or px) |
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76 mm-segmentation-distance = 1.81511847456 |
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77 # maximum distance between features for grouping (world distance unit or px) |
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78 max-distance = 5 |
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79 # minimum cosine of the angle between the velocity vectors for grouping |
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80 min-velocity-cosine = 0.8 |
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81 # minimum average number of features per frame to create a vehicle hypothesis |
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82 min-nfeatures-group = 3.16747690802 |
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83 # Road user classification |
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84 # min number of pixels in cropped image to classify by SVM |
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85 min-npixels-crop = 400 |
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86 # method to aggregate road user speed |
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87 speed-aggregation-method = median |
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88 # number of frames to ignore at both ends of a series (noisy) |
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89 nframes-ignore-at-ends = 2 |
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90 # quantile for the speed aggregation, if quantile is chosen |
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91 speed-aggregation-quantile = 50 |
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92 # speed value below which all classes are equiprobable (distributions give odd values there) (km/h) |
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93 min-speed-equiprobable = 3.33 |
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94 # filename of the general ped/cyc/veh SVM classifier |
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95 pbv-svm-filename = modelPBV.xml |
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96 # filename of the cyc/veh SVM classifier |
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97 bv-svm-filename = modelBV.xml |
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98 # maximum pedestrian speed (agregate: mean, median, 85th centile, etc.) 10 km/h |
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99 max-ped-speed = 10.0 |
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100 # maximum cyclist speed (agregate: mean, median, 85th centile, etc.) 30 km/h (3xped) |
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101 max-cyc-speed = 30.0 |
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102 # mean pedestrian speed and standard deviation (in a normal distribution) 4.91+-0.88 km/h |
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103 mean-ped-speed = 4.91 |
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104 std-ped-speed = 0.88 |
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105 # mean cyclist speed and standard deviation (in a log-normal distribution) 11.+-4.83 km/h |
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106 cyc-speed-loc = 2.31 |
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107 cyc-speed-scale = 0.42 |
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108 # mean vehicle speed and standard deviation (in a normal distribution) 18.45+-7.6 km/h |
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109 mean-veh-speed = 18.45 |
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110 std-veh-speed = 7.6 |
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111 # Safety analysis |
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112 # maximum speed when predicting future motion (km/h) |
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113 max-predicted-speed = 50 |
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114 # time horizon for collision prediction (s) |
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115 prediction-time-horizon = 5 |
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116 # collision distance threshold (m) |
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117 collision-distance = 1.8 |
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118 # option to compute crossing zones and predicted PET |
349
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119 crossing-zones = false |
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120 # prediction method: cv, na, ps |
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121 prediction-method = na |
349
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122 # number of predicted trajectories (use depends on prediction method) |
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123 npredicted-trajectories = 10 |
483
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124 # maximum acceleration for normal adaptation input symmetric distribution (m/s2) |
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125 max-normal-acceleration = 2 |
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126 # maximum steering for normal adaptation input symmetric distribution (rad/s) |
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127 max-normal-steering = 0.2 |
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128 # minimum acceleration for input distribution (m/s2) (extreme values used for evasive action distributions) |
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129 min-extreme-acceleration = -9.1 |
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130 # maximum acceleration for input distribution (m/s2) (extreme values used for evasive action distributions) |
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131 max-extreme-acceleration = 4.3 |
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132 # maximum steering for input distribution (rad/s) (extreme values used for evasive action distributions) |
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133 max-extreme-steering = 0.5 |
351
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134 # use feature positions and velocities for prediction |
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135 use-features-prediction = true |