Mercurial Hosting > traffic-intelligence
changeset 535:5ad2f51ae42f
cleaning up initialization of intrinsic matrix
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Sun, 29 Jun 2014 23:31:38 -0400 |
parents | d0419b1267dd |
children | 95276d310972 |
files | c/feature-based-tracking.cpp tracking.cfg |
diffstat | 2 files changed, 5 insertions(+), 4 deletions(-) [+] |
line wrap: on
line diff
diff -r d0419b1267dd -r 5ad2f51ae42f c/feature-based-tracking.cpp --- a/c/feature-based-tracking.cpp Sun Jun 29 14:37:30 2014 -0400 +++ b/c/feature-based-tracking.cpp Sun Jun 29 23:31:38 2014 -0400 @@ -73,8 +73,6 @@ Mat invHomography; if (params.display && !homography.empty()) invHomography = homography.inv(); - Mat intrinsicCameraMatrix = ::loadMat(params.intrinsicCameraFilename, " "); - //cout << intrinsicCameraMatrix << endl; float minTotalFeatureDisplacement = params.nDisplacements*params.minFeatureDisplacement; Size window = Size(params.windowSize, params.windowSize); @@ -114,9 +112,10 @@ ", height=" << videoSize.height << ", nframes=" << nFrames << endl; - Mat newIntrinsicCameraMatrix = intrinsicCameraMatrix.clone(); Mat map1, map2; if (params.undistort) { + Mat intrinsicCameraMatrix = ::loadMat(params.intrinsicCameraFilename, " "); + Mat newIntrinsicCameraMatrix = intrinsicCameraMatrix.clone(); videoSize = Size(static_cast<int>(round(videoSize.width*params.undistortedImageMultiplication)), static_cast<int>(round(videoSize.height*params.undistortedImageMultiplication))); newIntrinsicCameraMatrix.at<float>(0,2) = videoSize.width/2.; newIntrinsicCameraMatrix.at<float>(1,2) = videoSize.height/2.;
diff -r d0419b1267dd -r 5ad2f51ae42f tracking.cfg --- a/tracking.cfg Sun Jun 29 14:37:30 2014 -0400 +++ b/tracking.cfg Sun Jun 29 23:31:38 2014 -0400 @@ -19,7 +19,7 @@ # filename of the mask image (where features are detected) mask-filename = none # undistort the video for feature tracking -undistort = true +undistort = false # load features from database load-features = false # display trajectories on the video @@ -80,6 +80,8 @@ min-velocity-cosine = 0.8 # minimum average number of features per frame to create a vehicle hypothesis min-nfeatures-group = 3 +# Road user classification +# TODO # Safety analysis # maximum speed when predicting future motion (km/h) max-predicted-speed = 50