Sciweavers

Share
SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
9 years 9 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
10 years 2 months 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
10 years 2 months 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
10 years 2 months 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

4
posts
with
1434
views
1104profile views Browse  My Posts »
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
10 years 9 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...
books