Efficient region tracking with parametric models of geometry andillumination
Hager, G.D.
Belhumeur, P.N.
Dept. of Comput. Sci., Yale Univ., New Haven, CT ;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Oct 1998
Volume: 20,
Issue: 10
On page(s): 1025-1039
ISSN: 0162-8828
References Cited: 44
CODEN: ITPIDJ
INSPEC Accession Number: 6072824
Digital Object Identifier: 10.1109/34.722606
Current Version Published: 2002-08-06
Abstract
As an object moves through the field of view of a camera, the
images of the object may change dramatically. This is not simply due to
the translation of the object across the image plane; complications
arise due to the fact that the object undergoes changes in pose relative
to the viewing camera, in illumination relative to light sources, and
may even become partially or fully occluded. We develop an efficient
general framework for object tracking, which addresses each of these
complications. We first develop a computationally efficient method for
handling the geometric distortions produced by changes in pose. We then
combine geometry and illumination into an algorithm that tracks large
image regions using no more computation than would be required to track
with no accommodation for illumination changes. Finally, we augment
these methods with techniques from robust statistics and treat occluded
regions on the object as statistical outliers. Experimental results are
given to demonstrate the effectiveness of our methods
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
