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» Markov Random Field Modeling in Computer Vision
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BMVC
2002
13 years 11 months ago
Modelling Facial Behaviours
We consider the problem of learning how a person's face behaves in a long video sequence, with the aim of synthesising convincing sequences demonstrating the same behaviours....
Franck Bettinger, Timothy F. Cootes, Christopher J...
ECCV
2008
Springer
14 years 11 months ago
GeoS: Geodesic Image Segmentation
This paper presents GeoS, a new algorithm for the efficient segmentation of n-dimensional image and video data. The segmentation problem is cast as approximate energy minimization ...
Antonio Criminisi, Toby Sharp, Andrew Blake
CG
2005
Springer
13 years 9 months ago
Realistic synthesis of cao shu of Chinese calligraphy
In Chinese calligraphy cao shu is regarded as a kind of free form art which differs from other styles greatly in its less constrained strokes and brush textures. In this paper we ...
Jinhui Yu, Qunsheng Peng
ACCV
2006
Springer
14 years 3 months ago
Tracking Targets Via Particle Based Belief Propagation
We first formulate multiple targets tracking problem in a dynamic Markov network(DMN)which is derived from a MRFs for joint target state and a binary process for occlusion of dual...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
CEE
2010
119views more  CEE 2010»
13 years 9 months ago
Block-matching-based motion field generation utilizing directional edge displacement
A motion field generation algorithm using block matching of edge-flag histograms has been developed aiming at its application to motion recognition systems. Use of edge flags inste...
Hitoshi Hayakawa, Tadashi Shibata