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corrected bug in categorical value smoothing
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 25 Jun 2024 16:40:40 -0400
parents 9c27a0315c4d
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
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a9b2beef0db4 loading and assigning motion patterns works
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1 # filename of the video to process (can be images, eg image%04d.png)
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2 video-filename = laurier.avi
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3 # filename of the database where results are saved
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4 database-filename = laurier.sqlite
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5 # filename of the homography matrix
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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
935430b1d408 corrected mask bug in feature tracking, updated display-trajectories to display on undistorted image
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parents: 508
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18 interpolation-method = 1
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19 # filename of the mask image (where features are detected)
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20 mask-filename = none
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6f7fa0093162 adding parameter undistort in tracking.cfg
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21 # undistort the video for feature tracking
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5ad2f51ae42f cleaning up initialization of intrinsic matrix
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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 (world distance unit or 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 = 15
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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
775
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82 min-nfeatures-group = 3.16747690802
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83 # name of the configuration file for all classifier information
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84 classifier-filename = classifier.cfg
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85 # Safety analysis
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86 # maximum speed when predicting future motion (km/h)
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87 max-predicted-speed = 50
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88 # time horizon for collision prediction (s)
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89 prediction-time-horizon = 5.0
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90 # collision distance threshold (m)
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91 collision-distance = 1.8
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92 # option to compute crossing zones and predicted PET
349
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93 crossing-zones = false
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94 # prediction method: cv, cvd, na, ps, mp
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95 prediction-method = na
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96 # number of predicted trajectories (use depends on prediction method)
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97 npredicted-trajectories = 10
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98 # maximum acceleration for normal adaptation input symmetric distribution (m/s2)
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99 max-normal-acceleration = 2
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100 # maximum steering for normal adaptation input symmetric distribution (rad/s)
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101 max-normal-steering = 0.2
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102 # minimum acceleration for input distribution (m/s2) (extreme values used for evasive action distributions)
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103 min-extreme-acceleration = -9.1
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104 # maximum acceleration for input distribution (m/s2) (extreme values used for evasive action distributions)
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105 max-extreme-acceleration = 4.3
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106 # maximum steering for input distribution (rad/s) (extreme values used for evasive action distributions)
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107 max-extreme-steering = 0.5
351
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108 # use feature positions and velocities for prediction
352
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109 use-features-prediction = true
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110 # use constant speed (motion pattern based prediction)
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111 constant-speed = false
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112 # point distance threshold, for the chosen metric for trajectory matching using LCSS
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113 max-lcss-distance = 2.
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114 # distance metric for trajectory matching using LCSS
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115 lcss-metric = cityblock
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116 # similarity threshold for trajectory matching on normalized LCSS
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117 min-lcss-similarity = 0.4
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118 # minimum past feature length for past trajectory matching for motion prediction -> using min-feature-time