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» Method of Motion Data Processing Based on Manifold Learning
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NIPS
2007
13 years 8 months ago
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Zhengdong Lu, Miguel Á. Carreira-Perpi&ntil...
ICCV
2007
IEEE
14 years 1 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
ICPR
2010
IEEE
13 years 6 months ago
Learning Non-Linear Dynamical Systems by Alignment of Local Linear Models
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
Masao Joko, Yoshinobu Kawahara, Takehisa Yairi
MM
2004
ACM
152views Multimedia» more  MM 2004»
14 years 23 days ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...
PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
14 years 1 months ago
Subspace Regularization: A New Semi-supervised Learning Method
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...