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SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
10 years 7 months ago
Distance Preserving Dimension Reduction for Manifold Learning
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Hyunsoo Kim, Haesun Park, Hongyuan Zha
CVPR
2010
IEEE
11 years 12 days ago
Putting local features on a Manifold
Local features have proven very useful for recognition. Manifold learning has proven to be a very powerful tool in data analysis. However, manifold learning application for imag...
Marwan Torki and Ahmed Elgammal
EDUTAINMENT
2007
Springer
11 years 13 days ago
Method of Motion Data Processing Based on Manifold Learning
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
Fengxia Li, Tianyu Huang, Lijie Li
ACCV
2007
Springer
11 years 14 days ago
Analyzing Facial Expression by Fusing Manifolds
Feature representation and classiļ¬cation are two major issues in facial expression analysis. In the past, most methods used either holistic or local representation for analysis. ...
Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung

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Marwan A TorkiStudent, PhD
Rutgers University
Marwan A Torki
Marwan Torki is a Ph. D. student in computer science department at Rutgers University. He took his M.Sc. and B.Sc. in computer science from department of computer science, faculty ...
ICML
2007
IEEE
11 years 7 months ago
Non-isometric manifold learning: analysis and an algorithm
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
Piotr Dollár, Serge J. Belongie, Vincent Ra...
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