Many problems in computer vision can be modeled using
conditional Markov random fields (CRF). Since finding
the maximum a posteriori (MAP) solution in such models
is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
In this paper we propose a robust visual tracking method
by casting tracking as a sparse approximation problem in a
particle filter framework. In this framework, occlusion, corru...
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...
Our paper has two main contributions. Firstly, it presents a model for image sequences motivated by an image encoding perspective. It models accreted regions, where objects appear...
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...