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» Experimental Analysis of BRDF Models
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ICML
2005
IEEE
16 years 4 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
ECCV
2010
Springer
15 years 9 months ago
Dynamic Color Flow: A Motion-Adaptive Color Model for Object Segmentation in Video
Accurately modeling object colors, and features in general, plays a critical role in video segmentation and analysis. Commonly used color models, such as global Gaussian mixtures, ...
125
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AMDO
2006
Springer
15 years 7 months ago
Carrying Object Detection Using Pose Preserving Dynamic Shape Models
In this paper, we introduce a framework for carrying object detection in different people from different views using pose preserving dynamic shape models. We model dynamic shape de...
Chan-Su Lee, Ahmed M. Elgammal
DAGM
2006
Springer
15 years 7 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
CORR
2010
Springer
207views Education» more  CORR 2010»
15 years 3 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...