We address the problem of finding deformation between two images for the purpose of recognizing objects. The challenge is that discriminative features are often transformation-va...
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
We propose a method for reliably and accurately identifying anatomical landmarks in 3D CT volumes based on dense matching of parts-based graphical models. Such a system can be use...
Predicting human occupations in photos has great application potentials in intelligent services and systems. However, using traditional classification methods cannot reliably dis...
Foreground detection is at the core of many video processing tasks. In this paper, we propose a novel video foreground detection method that exploits the statistics of 3D space-tim...