PhD student in the computer
science department, Technion, Haifa, ISRAEL
Supervisor: Prof. Alfred
M. Bruckstein Go
to Freddy Bruckstein's web page
Robust camera motion estimation
"Causal Camera Motion Estimation
by Condensation and Robust Statistics Distance Measures"
PDF
version of the paper (Copyright: Springer-Verlag the publisher of ECCV
2004 proceedings)
Authors: Tal Nir (taln@cs.technion.ac.il)
and Alfred M. Bruckstein (freddy@cs.technion.ac.il)
Accepted to ECCV 2004
Synthetic
movie showing a smooth camera trajectory in a world of
40 stationary points with 20 outliers (random points).
Note that our brain can sense the camera motion as well as to seperate
the inliers from the outliers as long as the movie runs.
When the movie stops the seperation of inliers/outliers is lost.
The movie sequence analyzed in the paper (Movie 1):
Download Movie 1 in good quality JPEG images
Watch Movie 1 with feature tracking results
Download C code, feature tracking and scene structure data
The features were tracked using a Kanade-Lucas-Tomasi type feature tracker upgraded to color image sequences.
The middle of the letter B is marked by a big yellow cross.
The rest of the features were manually classified:
The inliers are marked as yellow crosses.
The outliers are marked by purple crosses.
Movie 2 (with the same scene structure):
Download Movie 2 in good quality JPEG images
Watch Movie 2 with feature tracking results
Feature tracking data for this movie can be found together with the C code
Movie 3 (with the same scene structure):
Download Movie 3 in good quality JPEG images
Watch Movie 3 with feature tracking results
Feature tracking data for this movie can be found together with the C code
Movie 4 (with the same scene structure):
Download Movie 4 in good quality JPEG images
(No feature tracking data for this movie yet)