视频跟踪论文
We consider the problem of visual tracking of regions of interest
in a sequence of motion blurred images. Traditional
methods couple tracking with deblurring in order to correctly
account for the effects of motion blur. Such coupling
is usually appropriate, but computationally wasteful when
visual tracking is the lone objective. Instead of deblurring
images, we propose to match regions by blurring them. The
matching score for two image regions is governed by a cost
function that only involves the region deformation parameters
and two motion blur vectors. We present an efficient algorithm
to minimize the proposed cost function and demonstrate
it on sequences of real blurred images.
