BibTeX
@MISC{_automaticrectification,
author = {},
title = {AUTOMATIC RECTIFICATION OF LONG IMAGE SEQUENCES},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
This paper addresses the problem of automatically computing homographies between successive frames in image sequences and compensating for the panning, tilting and zooming of the cameras. A homography is a projective mapping between two image planes and describes the transformation created by a fixed camera as it pans, tilts, rotates, and zooms around its optical centre. Our algorithm achieves improved robustness for large motions by combining elements of two previous approaches: it first computes the local displacements of image features using the Kanade-Lucas-Tomasi (KLT) tracker and determines local matches. The majority of these features are selected by RANSAC and give the initial estimate of the homography. Our modelbased correction system then compensates for remaining projection errors in the image to rink mapping. The system is demonstrated on a digitized sequence of an NHL hockey game, and it is capable of analyzing long sequences of consecutive frames from broadcast video by mapping them into the rink coordinates. 1.
Keyphrases
automatic rectification long image sequence consecutive frame algorithm achieves successive frame modelbased correction system image feature optical centre large motion long sequence projection error image plane broadcast video nhl hockey game fixed camera image sequence initial estimate digitized sequence projective mapping previous approach local displacement determines local match
