This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...
A key problem in video content analysis using dynamic graphical models is to learn a suitable model structure given some observed visual data. We propose a Completed Likelihood AI...
We present a variational approach for segmenting the image plane into regions of piecewise parametric motion given two or more frames from an image sequence. Our model is based on ...
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Semantic video indexing is the first step towards automatic video retrieval and personalization. We propose a data-driven stochastic modeling approach to perform both video segmen...