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» Markov Random Field Modeling in Computer Vision
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AAAI
1994
13 years 10 months ago
Control Strategies for a Stochastic Planner
We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on s...
Jonathan Tash, Stuart J. Russell
CVPR
2007
IEEE
14 years 11 months ago
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning
A well-built dataset is a necessary starting point for advanced computer vision research. It plays a crucial role in evaluation and provides a continuous challenge to stateof-the-...
Li-Jia Li, Gang Wang, Fei-Fei Li 0002
CVPR
2010
IEEE
14 years 5 months ago
Modeling Mutual Context of Object and Human Pose in Human-Object Interaction Activities
Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in ac...
Bangpeng Yao, Li Fei-Fei
ACIVS
2007
Springer
14 years 1 months ago
Joint Domain-Range Modeling of Dynamic Scenes with Adaptive Kernel Bandwidth
Abstract. The first step in various computer vision applications is a detection of moving objects. The prevalent pixel-wise models regard image pixels as independent random process...
Borislav Antic, Vladimir S. Crnojevic
CAIP
2009
Springer
202views Image Analysis» more  CAIP 2009»
13 years 7 months ago
Near-Regular Texture Synthesis
This paper describes a method for seamless enlargement or editing of difficult colour textures containing simultaneously both regular periodic and stochastic components. Such textu...
Michal Haindl, Martin Hatka