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» 2D Shape Recognition by Hidden Markov Models
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SCVMA
2004
Springer
15 years 5 months ago
2D Motion Description and Contextual Motion Analysis: Issues and New Models
Abstract. In this paper, several important issues related to visual motion analysis are addressed with a focus on the type of motion information to be estimated and the way context...
Patrick Bouthemy
PRL
2000
148views more  PRL 2000»
14 years 11 months ago
One-dimensional representation of two-dimensional information for HMM based handwriting recognition
: In this study, we introduce a set of one-dimensional features to represent two dimensional shape information for HMM (Hidden Markov Model) based handwritten optical character rec...
Nafiz Arica, Fatos T. Yarman-Vural
FGR
2011
IEEE
267views Biometrics» more  FGR 2011»
14 years 3 months ago
A dynamic approach to the recognition of 3D facial expressions and their temporal models
— In this paper we propose a method that exploits 3D motion-based features between frames of 3D facial geometry sequences for dynamic facial expression recognition. An expressive...
Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic,...
FGR
2006
IEEE
163views Biometrics» more  FGR 2006»
15 years 5 months ago
Human Action Recognition Using Multi-View Image Sequences Features
Recognizing human action from image sequences is an active area of research in computer vision. In this paper, we present a novel method for human action recognition from image se...
Mohiuddin Ahmad, Seong-Whan Lee
ICML
2008
IEEE
16 years 13 days ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr