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» Variational Bayesian image modelling
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ICCV
2005
IEEE
16 years 5 months ago
Bottom-up/Top-Down Image Parsing by Attribute Graph Grammar
In this paper, we present an attribute graph grammar for image parsing on scenes with man-made objects, such as buildings, hallways, kitchens, and living rooms. We choose one clas...
Feng Han, Song Chun Zhu
PCI
2005
Springer
15 years 9 months ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
172
Voted
PAMI
2007
185views more  PAMI 2007»
15 years 2 months ago
A Two-Level Generative Model for Cloth Representation and Shape from Shading
In this paper we present a two-level generative model for representing the images and surface depth maps of drapery and clothes. The upper level consists of a number of folds whic...
Feng Han, Song Chun Zhu
127
Voted
FGR
2004
IEEE
129views Biometrics» more  FGR 2004»
15 years 7 months ago
Multiple Frame Motion Inference Using Belief Propagation
We present an algorithm for automatic inference of human upper body motion. A graph model is proposed for inferring human motion, and motion inference is posed as a mapping proble...
Jiang Gao, Jianbo Shi
206
Voted
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge