Mercurial > hg > nsaunier > traffic-intelligence

annotate tracking.cfg @ 464:dcc821b98efc

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integrated and reorganized Sohail s work on exact ttc computation
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Sun, 23 Feb 2014 23:18:08 -0500
parents ca5784652d57
children 30b3455978d9
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1 # filename of the video to process
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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 mask image (where features are detected)
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8 mask-filename = none
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9 # load features from database
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10 load-features = false
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11 # display trajectories on the video
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12 display = false
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13 # original video frame rate (number of frames/s)
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14 video-fps = 29.97
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15 # number of digits of precision for all measurements derived from video
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16 # measurement-precision = 3
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17 # first frame to process
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18 frame1 = 0
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19 # number of frame to process: 0 means processing all frames
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20 nframes = 0
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21 # feature tracking
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22 # maximum number of features added at each frame
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23 max-nfeatures = 1000
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24 # quality level of the good features to track
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25 feature-quality = 0.1
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26 # minimum distance between features
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27 min-feature-distanceklt = 5
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28 # size of the search window at each pyramid level
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29 window-size = 7
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30 # use of Harris corner detector
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31 use-harris-detector = false
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32 # k parameter to detect good features to track (OpenCV)
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33 k = 0.4
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34 # maximal pyramid level in the feature tracking algorithm
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35 pyramid-level = 5
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36 # number of displacement to test minimum feature motion
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37 ndisplacements = 3
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38 # minimum displacement to keep features
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39 min-feature-displacement = 0.05
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40 # maximum feature acceleration
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41 acceleration-bound = 3
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42 # maximum feature deviation
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43 deviation-bound = 0.6
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44 # number of frames to smooth positions (half window)
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45 smoothing-halfwidth = 5
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46 # number of frames to compute velocities
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47 #nframes-velocity = 5
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48 # maximum number of iterations to stop feature tracking
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49 max-number-iterations = 20
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50 # minimum error to reach to stop feature tracking
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51 min-tracking-error = 0.3
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52 # minimum eigen value of a 2x2 normal matrix of optical flow equations
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53 min-feature-eig-threshold = 1e-4
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54 # minimum length of a feature (number of frames) to consider a feature for grouping
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55 min-feature-time = 20
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56 # Min Max similarity parameters (Beymer et al. method)
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57 # connection distance in feature grouping
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58 mm-connection-distance = 3.75
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59 # segmentation distance in feature grouping
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60 mm-segmentation-distance = 1.5
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61 # maximum distance between features for grouping
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62 max-distance = 5
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63 # minimum cosine of the angle between the velocity vectors for grouping
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64 min-velocity-cosine = 0.8
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65 # minimum average number of features per frame to create a vehicle hypothesis
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66 min-nfeatures-group = 3
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67 # Safety analysis
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68 # maximum speed when predicting future motion (km/h)
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69 max-predicted-speed = 50
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70 # time horizon for collision prediction (s)
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71 prediction-time-horizon = 5
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72 # collision distance threshold (m)
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73 collision-distance = 1.8
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74 # option to compute crossing zones and predicted PET
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75 crossing-zones = false
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76 # prediction method: cv, na, ps
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77 prediction-method = na
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78 # number of predicted trajectories (use depends on prediction method)
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79 npredicted-trajectories = 10
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80 # minimum acceleration for input distribution (m/s2) (used only for evasive action distributions)
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81 min-acceleration = -9.1
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82 # maximum acceleration for input distribution (m/s2)
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83 max-acceleration = 2
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84 # maximum steering for input distribution (rad/s)
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85 max-steering = 0.5
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86 # use feature positions and velocities for prediction
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87 use-features-prediction = true