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PR
2007
137views more  PR 2007»
13 years 9 months ago
Boosted manifold principal angles for image set-based recognition
In this paper we address the problem of classifying vector sets. We motivate and introduce a novel method based on comparisons between corresponding vector subspaces. In particula...
Tae-Kyun Kim, Ognjen Arandjelovic, Roberto Cipolla
MICCAI
2010
Springer
13 years 8 months ago
Nonlinear Embedding towards Articulated Spine Shape Inference Using Higher-Order MRFs
In this paper we introduce a novel approach for inferring articulated spine models from images. A low-dimensional manifold embedding is created from a training set of prior mesh mo...
Samuel Kadoury, Nikos Paragios
ICPR
2010
IEEE
13 years 8 months ago
Learning Non-Linear Dynamical Systems by Alignment of Local Linear Models
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
Masao Joko, Yoshinobu Kawahara, Takehisa Yairi
JNS
2007
85views more  JNS 2007»
13 years 9 months ago
Long-Time Accuracy for Approximate Slow Manifolds in a Finite-Dimensional Model of Balance
We study the slow singular limit for planar anharmonic oscillatory motion of a charged particle under the influence of a perpendicular magnetic field when the mass of the particl...
G. Gottwald, M. Oliver, N. Tecu
ECCV
2004
Springer
14 years 11 months ago
Transformation-Invariant Embedding for Image Analysis
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
Ali Ghodsi, Jiayuan Huang, Dale Schuurmans