We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
We study the problem of generating plausible interpretations
of a scene from a collection of line segments automatically
extracted from a single indoor image. We show that
we ca...
— There has been significant progress recently in object recognition research, but many of the current approaches still fail for object classes with few distinctive features, an...
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
A novel scheme is proposed for achieving motion segmentation in low-frame rate videos, with application to temporal super resolution. Probabilistic generative models are commonly ...