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» Robust Principal Component Analysis for Computer Vision
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ICPR
2002
IEEE
15 years 11 months ago
Reliable and Fast Eye Finding in Close-up Images
This paper describes a method for quickly and robustly localizing the iris and pupil boundaries of a human eye in close-up images. Such an algorithm can be critical for iris ident...
Theodore A. Camus, Richard P. Wildes
ALT
2010
Springer
14 years 7 months ago
A Spectral Approach for Probabilistic Grammatical Inference on Trees
We focus on the estimation of a probability distribution over a set of trees. We consider here the class of distributions computed by weighted automata - a strict generalization of...
Raphaël Bailly, Amaury Habrard, Franço...
MICCAI
2009
Springer
15 years 11 months ago
Building Shape Models from Lousy Data
Statistical shape models have gained widespread use in medical image analysis. In order for such models to be statistically meaningful, a large number of data sets have to be inclu...
Marcel Lüthi, Thomas Albrecht, Thomas Vetter
ICMCS
2006
IEEE
161views Multimedia» more  ICMCS 2006»
15 years 4 months ago
Emotion Recognition from Noisy Speech
This paper presents an emotion recognition system from clean and noisy speech. Geodesic distance was adopted to preserve the intrinsic geometry of emotional speech. Based on the g...
Mingyu You, Chun Chen, Jiajun Bu, Jia Liu, Jianhua...
AUSAI
2005
Springer
15 years 4 months ago
Resampling LDA/QR and PCA+LDA for Face Recognition
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
Jun Liu, Songcan Chen