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» Bayesian Human Segmentation in Crowded Situations
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CVPR
2003
IEEE
14 years 4 months ago
Bayesian Human Segmentation in Crowded Situations
Problem of segmenting individual humans in crowded situations from stationary video camera sequences is exacerbated by object inter-occlusion. We pose this problem as a “model-b...
Tao Zhao, Ramakant Nevatia
PAMI
2008
188views more  PAMI 2008»
13 years 11 months ago
Segmentation and Tracking of Multiple Humans in Crowded Environments
Segmentation and tracking of multiple humans in crowded situations is made difficult by interobject occlusion. We propose a model-based approach to interpret the image observations...
Tao Zhao, Ramakant Nevatia, Bo Wu
WSC
2008
14 years 1 months ago
Integrated human decision making model under Belief-Desire-Intention framework for crowd simulation
An integrated Belief-Desire-Intention (BDI) modeling framework is proposed for human decision making and planning, whose sub-modules are based on Bayesian belief network (BBN), De...
Seungho Lee, Young-Jun Son
ICCV
2007
IEEE
15 years 26 days ago
Hierarchical Part-Template Matching for Human Detection and Segmentation
Local part-based human detectors are capable of handling partial occlusions efficiently and modeling shape articulations flexibly, while global shape template-based human detector...
Zhe Lin, Larry S. Davis, David S. Doermann, Daniel...
IJISTA
2006
113views more  IJISTA 2006»
13 years 11 months ago
Extraction of mid-level semantics from gesture videos using a Bayesian network
In this paper a method for extraction of mid-level semantics from sign language videos is proposed, by employing high level domain knowledge. The semantics concern labeling of the ...
Dimitrios I. Kosmopoulos, Ilias Maglogiannis