Mercurial Hosting > traffic-intelligence
view tracking.cfg @ 402:f29204e68aab
function to generate homography from PDTV Tsai format and script to generate trajectories from sqlite bounding boxes
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Mon, 29 Jul 2013 19:45:43 -0400 |
parents | 72aa44072093 |
children | ca5784652d57 |
line wrap: on
line source
# filename of the video to process video-filename = laurier.avi # filename of the database where results are saved database-filename = laurier.sqlite # filename of the homography matrix homography-filename = laurier-homography.txt # filename of the mask image (where features are detected) mask-filename = none # load features from database load-features = false # display trajectories on the video display = false # original video frame rate (number of frames/s) video-fps = 29.97 # number of digits of precision for all measurements derived from video # measurement-precision = 3 # first frame to process frame1 = 0 # number of frame to process: 0 means processing all frames nframes = 0 # feature tracking # maximum number of features added at each frame max-nfeatures = 1000 # quality level of the good features to track feature-quality = 0.1 # minimum distance between features min-feature-distanceklt = 5 # size of the search window at each pyramid level window-size = 7 # use of Harris corner detector use-harris-detector = false # k parameter to detect good features to track (OpenCV) k = 0.4 # maximal pyramid level in the feature tracking algorithm pyramid-level = 5 # number of displacement to test minimum feature motion ndisplacements = 3 # minimum displacement to keep features min-feature-displacement = 0.05 # maximum feature acceleration acceleration-bound = 3 # maximum feature deviation deviation-bound = 0.6 # number of frames to smooth positions (half window) smoothing-halfwidth = 5 # number of frames to compute velocities #nframes-velocity = 5 # maximum number of iterations to stop feature tracking max-number-iterations = 20 # minimum error to reach to stop feature tracking min-tracking-error = 0.3 # minimum length of a feature (number of frames) to consider a feature for grouping min-feature-time = 20 # Min Max similarity parameters (Beymer et al. method) # connection distance in feature grouping mm-connection-distance = 3.75 # segmentation distance in feature grouping mm-segmentation-distance = 1.5 # maximum distance between features for grouping max-distance = 5 # minimum cosine of the angle between the velocity vectors for grouping min-velocity-cosine = 0.8 # minimum average number of features per frame to create a vehicle hypothesis min-nfeatures-group = 3 # Safety analysis # maximum speed when predicting future motion (km/h) max-predicted-speed = 50 # time horizon for collision prediction (s) prediction-time-horizon = 5 # collision distance threshold (m) collision-distance = 1.8 # option to compute crossing zones and predicted PET crossing-zones = false # prediction method: cv, na, ps prediction-method = na # number of predicted trajectories (use depends on prediction method) npredicted-trajectories = 10 # minimum acceleration for input distribution (m/s2) (used only for evasive action distributions) min-acceleration = -9.1 # maximum acceleration for input distribution (m/s2) max-acceleration = 2 # maximum steering for input distribution (rad/s) max-steering = 0.5 # use feature positions and velocities for prediction use-features-prediction = true