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comparison tracking.cfg @ 775:56153d439f8c dev

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updated sample parameters in tracking.cfg to good parameters from the TRB paper Morse et al 2016
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 05 Feb 2016 12:28:18 -0500
parents 94b291a5f933
children f7cf43b5ad3b 21f10332c72b
comparison
equal deleted inserted replaced
774:b6d3bf350789 775:56153d439f8c
34 nframes = 0 34 nframes = 0
35 # feature tracking 35 # feature tracking
36 # maximum number of features added at each frame 36 # maximum number of features added at each frame
37 max-nfeatures = 1000 37 max-nfeatures = 1000
38 # quality level of the good features to track 38 # quality level of the good features to track
39 feature-quality = 0.1 39 feature-quality = 0.0812219538558
40 # minimum distance between features (px) 40 # minimum distance between features (px)
41 min-feature-distanceklt = 5 41 min-feature-distanceklt = 3.54964337411
42 # size of the block for feature characteristics (px) 42 # size of the block for feature characteristics (px)
43 block-size = 7 43 block-size = 7
44 # use of Harris corner detector 44 # use of Harris corner detector
45 use-harris-detector = false 45 use-harris-detector = false
46 # k parameter to detect good features to track (OpenCV) 46 # k parameter to detect good features to track (OpenCV)
47 k = 0.4 47 k = 0.4
48 # size of the search window at each pyramid level (px) 48 # size of the search window at each pyramid level (px)
49 window-size = 7 49 window-size = 6
50 # maximal pyramid level in the feature tracking algorithm 50 # maximal pyramid level in the feature tracking algorithm
51 pyramid-level = 5 51 pyramid-level = 5
52 # number of displacement to test minimum feature motion 52 # number of displacement to test minimum feature motion
53 ndisplacements = 3 53 ndisplacements = 3
54 # minimum displacement to keep features (px) 54 # minimum displacement to keep features (px)
62 # number of frames to compute velocities 62 # number of frames to compute velocities
63 #nframes-velocity = 5 63 #nframes-velocity = 5
64 # maximum number of iterations to stop feature tracking 64 # maximum number of iterations to stop feature tracking
65 max-number-iterations = 20 65 max-number-iterations = 20
66 # minimum error to reach to stop feature tracking 66 # minimum error to reach to stop feature tracking
67 min-tracking-error = 0.3 67 min-tracking-error = 0.183328975142
68 # minimum eigen value of a 2x2 normal matrix of optical flow equations 68 # minimum eigen value of a 2x2 normal matrix of optical flow equations
69 min-feature-eig-threshold = 1e-4 69 min-feature-eig-threshold = 1e-4
70 # minimum length of a feature (number of frames) to consider a feature for grouping 70 # minimum length of a feature (number of frames) to consider a feature for grouping
71 min-feature-time = 20 71 min-feature-time = 9
72 # Min Max similarity parameters (Beymer et al. method) 72 # Min Max similarity parameters (Beymer et al. method)
73 # connection distance in feature grouping (world distance unit or px) 73 # connection distance in feature grouping (world distance unit or px)
74 mm-connection-distance = 3.75 74 mm-connection-distance = 2.68813545522
75 # segmentation distance in feature grouping (world distance unit or px) 75 # segmentation distance in feature grouping (world distance unit or px)
76 mm-segmentation-distance = 1.5 76 mm-segmentation-distance = 1.81511847456
77 # maximum distance between features for grouping (world distance unit or px) 77 # maximum distance between features for grouping (world distance unit or px)
78 max-distance = 5 78 max-distance = 5
79 # minimum cosine of the angle between the velocity vectors for grouping 79 # minimum cosine of the angle between the velocity vectors for grouping
80 min-velocity-cosine = 0.8 80 min-velocity-cosine = 0.8
81 # minimum average number of features per frame to create a vehicle hypothesis 81 # minimum average number of features per frame to create a vehicle hypothesis
82 min-nfeatures-group = 3 82 min-nfeatures-group = 3.16747690802
83 # Road user classification 83 # Road user classification
84 # min number of pixels in cropped image to classify by SVM 84 # min number of pixels in cropped image to classify by SVM
85 min-npixels-crop = 400 85 min-npixels-crop = 400
86 # method to aggregate road user speed 86 # method to aggregate road user speed
87 speed-aggregation-method = median 87 speed-aggregation-method = median