We propose a principled framework to model persistent motion in dynamic scenes. In contrast to previous efforts on object tracking and optical flow estimation that focus on local...
Human motion can be understood on many levels. The most basic level is the notion that humans are collections of things that have predictable visual appearance. Next is the notion...
Christopher Richard Wren, Brian P. Clarkson, Alex ...
Robust tracking of abrupt motion is a challenging task
in computer vision due to the large motion uncertainty. In
this paper, we propose a stochastic approximation Monte
Carlo (...
Owing to the lack of resolution of the measurement and the randomness inherent in the signal and the measuring devices, the measurement noise is often signal-dependent. Although t...
In this paper, we describe a minimal mean square error (MMSE) optimal interpolation filter for discrete random signals. We explicitly derive the interpolation filter for a firs...
Eija Johansson, Marie Strom, Mats Viberg, Lennart ...