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Paper Abstract and Keywords
Presentation 2008-03-13 15:20
Learning and Inference of Probabilistic Causal Structure Model for Indoor Behavior Prediction of Infants
Satoshi Kawata (Tohoku Univ.), Yoichi Motomura, Yoshifumi Nishida (AIST), Shouzou Ishikawa (Metropolitan College of Industrial Technology), Kazuyuki Tanaka (Tohoku Univ.) NC2007-159
Abstract (in Japanese) (See Japanese page) 
(in English) In order to contribute to saving children exposed to daily dangers,
monitoring children's everyday behavior is essential for the paradigms of infant risk prevention.
In this research, we introduce a statistical lerning to predict infant behavioral models.
With the rapid progress in computer-aided processing, we have come to make use of precise graphical models based on calculation using Bayesian networks.
Utilizing diverse graphical models will lead us to cover various prior knowledge dwelling in the real world. In this paper,
we model probabilistic causal structure chronologically making use of diverse dynamic images and ultrasound location sensor data based on Bayesian Network.
Compared with the maximum likelihood estimator dealing with machine learning,
this model will give us broader perspective to predict expected human behavior more precisely in daily life.
Keyword (in Japanese) (See Japanese page) 
(in English) Bayesian Networks / Bayes Estimation / Behavior Recognition / Image Processing / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 542, NC2007-159, pp. 279-282, March 2008.
Paper # NC2007-159 
Date of Issue 2008-03-05 (NC) 
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 NC2007-159

Conference Information
Committee NC MBE  
Conference Date 2008-03-12 - 2008-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa Univ 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2008-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Learning and Inference of Probabilistic Causal Structure Model for Indoor Behavior Prediction of Infants 
Sub Title (in English)  
Keyword(1) Bayesian Networks  
Keyword(2) Bayes Estimation  
Keyword(3) Behavior Recognition  
Keyword(4) Image Processing  
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Keyword(6)  
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Keyword(8)  
1st Author's Name Satoshi Kawata  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Yoichi Motomura  
2nd Author's Affiliation National Institute of Advanced Industrial Science and Technology (AIST)
3rd Author's Name Yoshifumi Nishida  
3rd Author's Affiliation National Institute of Advanced Industrial Science and Technology (AIST)
4th Author's Name Shouzou Ishikawa  
4th Author's Affiliation Tokyo Metropolitan College of Industrial Technology (Metropolitan College of Industrial Technology)
5th Author's Name Kazuyuki Tanaka  
5th Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2008-03-13 15:20:00 
Presentation Time 20 minutes 
Registration for NC 
Paper # NC2007-159 
Volume (vol) vol.107 
Number (no) no.542 
Page pp.279-282 
#Pages 4 
Date of Issue 2008-03-05 (NC) 

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