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» Unsupervised Learning of Human Motion Models
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CVPR
2006
IEEE
15 years 11 months ago
Dynamic Appearance Modeling for Human Tracking
Dynamic appearance is one of the most important cues for tracking and identifying moving people. However, direct modeling spatio-temporal variations of such appearance is often a ...
Hwasup Lim, Octavia I. Camps, Mario Sznaier, Vlad ...
CRV
2008
IEEE
295views Robotics» more  CRV 2008»
15 years 4 months ago
3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
Kooksang Moon, Vladimir Pavlovic
ACL
2006
14 years 11 months ago
Learning Transliteration Lexicons from the Web
This paper presents an adaptive learning framework for Phonetic Similarity Modeling (PSM) that supports the automatic construction of transliteration lexicons. The learning algori...
Jin-Shea Kuo, Haizhou Li, Ying-Kuei Yang
CVPR
2009
IEEE
1132views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Observable Subspaces for 3D Human Motion Recovery
The articulated body models used to represent human motion typically have many degrees of freedom, usually expressed as joint angles that are highly correlated. T...
Andrea Fossati (EPFL), Mathieu Salzmann (Universit...
CVPR
2012
IEEE
13 years 1 days ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann