In this paper, a region-based spatio-temporal Markov random field (STMRF) model is proposed to segment moving objects semantically. The STMRF model combines segmentation results o...
In this paper, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse mat...
Csaba Benedek, Tamas Sziranyi, Zoltan Kato, and Jo...
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
This paper presents Bayesian edge inference (BEI), a
single-frame super-resolution method explicitly grounded in
Bayesian inference that addresses issues common to existing
meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...