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» Nonlinear principal component analysis of noisy data
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ICIP
2007
IEEE
15 years 1 months ago
Real-Time Pedestrian Detection using Eigenflow
We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e. the ...
Dhiraj Goel, Tsuhan Chen
PAMI
2010
192views more  PAMI 2010»
14 years 8 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens
CHI
2009
ACM
15 years 10 months ago
Correlations among prototypical usability metrics: evidence for the construct of usability
Correlations between prototypical usability metrics from 90 distinct usability tests were strong when measured at the task-level (r between .44 and .60). Using test-level satisfac...
Jeff Sauro, James R. Lewis
ICIAR
2004
Springer
15 years 3 months ago
Three-Dimensional Face Recognition: A Fishersurface Approach
Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...
Thomas Heseltine, Nick Pears, Jim Austin
JMM2
2006
110views more  JMM2 2006»
14 years 9 months ago
Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition
We propose a technique for gait recognition from motion capture data based on two successive stages of principal component analysis (PCA) on kinematic data. The first stage of PCA ...
Sandhitsu R. Das, Robert C. Wilson, Maciej T. Laza...