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» Experimental Analysis of BRDF Models
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ICML
2005
IEEE
16 years 7 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 11 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, ...
AMDO
2006
Springer
15 years 10 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 10 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 6 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...