# HG changeset patch
# User Nicolas Saunier <nicolas.saunier@polymtl.ca>
# Date 1404099098 14400
# Node ID 5ad2f51ae42fb32905a0c62c56a4f5a2c2c458d6
# Parent  d0419b1267ddf78b0f26d21ff00c322f249c3975
cleaning up initialization of intrinsic matrix

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