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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
SMI
2005
IEEE
111views Image Analysis» more  SMI 2005»
14 years 1 months ago
Rational Spherical Splines for Genus Zero Shape Modeling
Traditional approaches for modeling a closed manifold surface with either regular tensor-product or triangular splines (defined over an open planar domain) require decomposing th...
Ying He 0001, Xianfeng Gu, Hong Qin
VISUALIZATION
1997
IEEE
13 years 11 months ago
Simplifying polygonal models using successive mappings
: We present the use of mapping functions to automatically generate levels of detail with known error bounds for polygonal models. We develop a piece-wise linear mapping function f...
Jonathan D. Cohen, Dinesh Manocha, Marc Olano
CRV
2006
IEEE
176views Robotics» more  CRV 2006»
13 years 9 months ago
Stereo Retinex
The retinex algorithm for lightness and color constancy is extended to include 3-dimensional spatial information reconstructed from a stereo image. A key aspect of traditional ret...
Weihua Xiong, Brian V. Funt
ECCV
2004
Springer
14 years 9 months ago
Multiple View Feature Descriptors from Image Sequences via Kernel Principal Component Analysis
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...