Mercurial Hosting > traffic-intelligence
comparison tracking.cfg @ 537:6c264b914846
work on classification parameters
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Wed, 02 Jul 2014 17:43:16 -0400 |
parents | 5ad2f51ae42f |
children | 5800a87f11ae |
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536:95276d310972 | 537:6c264b914846 |
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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 |
83 # Road user classification | 83 # Road user classification |
84 # TODO | 84 # filename of the general ped/cyc/veh SVM classifier |
85 pbv-svm-filename = modelPBV.xml | |
86 # filename of the cyc/veh SVM classifier | |
87 pbv-svm-filename = modelBV.xml | |
88 # maximum pedestrian speed (agregate: mean, median, 85th centile, etc.) 3.6 m/s | |
89 max-ped-speed = 0.12 | |
90 # maximum cyclist speed (agregate: mean, median, 85th centile, etc.) 10.8 m/s (3xped) | |
91 max-cyc-speed = 0.36 | |
92 # mean pedestrian speed and standard deviation (in a normal distribution) 1.36+-0.24 m/s | |
93 mean-ped-speed = 0.45 | |
94 std-ped-speed = 0.008 | |
95 # mean cyclist speed and standard deviation (in a log-normal distribution) 1.36+-0.24 m/s | |
96 mean-cyc-speed = 0.45 | |
97 std-cyc-speed = 0.008 | |
98 # mean vehicle speed and standard deviation (in a normal distribution) 5.12+-2.11 m/s | |
99 mean-veh-speed = 0.17 | |
100 std-veh-speed = 0.07 | |
85 # Safety analysis | 101 # Safety analysis |
86 # maximum speed when predicting future motion (km/h) | 102 # maximum speed when predicting future motion (km/h) |
87 max-predicted-speed = 50 | 103 max-predicted-speed = 50 |
88 # time horizon for collision prediction (s) | 104 # time horizon for collision prediction (s) |
89 prediction-time-horizon = 5 | 105 prediction-time-horizon = 5 |