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Paper Abstract and Keywords
Presentation 2011-12-16 16:30
Nonparametric Bayesian State Estimation by Detecting Change Points and Sharing Segments on Time Series Data
Masamichi Shimosaka, Yuichi Moriya, Rui Fukui, Tomomasa Sato (Univ. of Tokyo) PRMU2011-145
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a novel framework for estimating state spaces where the size is unknown. The proposed framework resolves rapid transitions among redundant states, which are common problem with nonparametric state estimation models. Our approach is based on segmentation and segment categorization, while another approach is sticky extension (Fox et al., 2008). We provide an inference strategy for hidden Markov model and switching linear dynamical system. By using synthetic data and motion capture data, we demonstrate that our method is superior over conventional methods in view of extracting motion sequences and inference efficiency.
Keyword (in Japanese) (See Japanese page) 
(in English) Dirichlet process mixtures / hidden Markov model / switching linear dynamical system / segmentation / state estimation / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 353, PRMU2011-145, pp. 119-124, Dec. 2011.
Paper # PRMU2011-145 
Date of Issue 2011-12-08 (PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2011-145

Conference Information
Committee PRMU FM  
Conference Date 2011-12-15 - 2011-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Hamamatsu Campus, Shizuoka Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2011-12-PRMU-FM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Nonparametric Bayesian State Estimation by Detecting Change Points and Sharing Segments on Time Series Data 
Sub Title (in English)  
Keyword(1) Dirichlet process mixtures  
Keyword(2) hidden Markov model  
Keyword(3) switching linear dynamical system  
Keyword(4) segmentation  
Keyword(5) state estimation  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Masamichi Shimosaka  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo)
2nd Author's Name Yuichi Moriya  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
3rd Author's Name Rui Fukui  
3rd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
4th Author's Name Tomomasa Sato  
4th Author's Affiliation The University of Tokyo (Univ. of Tokyo)
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Speaker Author-2 
Date Time 2011-12-16 16:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2011-145 
Volume (vol) vol.111 
Number (no) no.353 
Page pp.119-124 
#Pages 6 
Date of Issue 2011-12-08 (PRMU) 

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