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Paper Abstract and Keywords
Presentation 2018-09-27 15:15
[Special Talk] Coded Acquistion of Light Fields -- From Basis Representation to Deep Learning --
Keita Takahashi (Nagoya Univ.) LOIS2018-15 IE2018-35 EMM2018-54
Abstract (in Japanese) (See Japanese page) 
(in English) A light field, which is often understood as a set of dense multi-view images, has been utilized in various 2D/3D applications. Acquiring a light field is a challenging task due to the amount of data. To make the acquisition process efficient, coded aperture cameras were successfully adopted; using these cameras, a light field is computationally reconstructed from several images that are acquired with different aperture patterns. However, it is still difficult to reconstruct a high-quality light field from only a few acquired images. Previously, this problem has often been discussed from the context of compressed sensing (CS), where sparse representations on a pre-trained dictionary or basis are explored to reconstruct the light field. We first took an approach to this problem from the perspective of principal component analysis (PCA) and non-negative matrix factorization (NMF), where only a small number of basis vectors are selected in advance based on the analysis of the training dataset. We also proposed a learning-based framework, where the entire pipeline of light field acquisition was formulated from the perspective of an auto-encoder that can be trained end-to-end by using a collection of training samples. We obtained promising results both with simulative experiments and a real camera prototype.
Keyword (in Japanese) (See Japanese page) 
(in English) Light field / Coded aperture / PCA / NMF / Deep learing / Compressed sensing / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 223, IE2018-35, pp. 29-30, Sept. 2018.
Paper # IE2018-35 
Date of Issue 2018-09-20 (LOIS, IE, EMM) 
ISSN 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 LOIS2018-15 IE2018-35 EMM2018-54

Conference Information
Committee IEE-CMN EMM LOIS IE ITE-ME  
Conference Date 2018-09-27 - 2018-09-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Beppu Int'l Convention Ctr. aka B-CON Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Multimedia Communication/System, Lifelog Applications, IP Broadcasting/Video Transmission, Media Security, Media Processing (AI, Deep Learning), etc. 
Paper Information
Registration To IE 
Conference Code 2018-09-CMN-EMM-LOIS-IE-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Coded Acquistion of Light Fields 
Sub Title (in English) From Basis Representation to Deep Learning 
Keyword(1) Light field  
Keyword(2) Coded aperture  
Keyword(3) PCA  
Keyword(4) NMF  
Keyword(5) Deep learing  
Keyword(6) Compressed sensing  
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Keyword(8)  
1st Author's Name Keita Takahashi  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2018-09-27 15:15:00 
Presentation Time 35 minutes 
Registration for IE 
Paper # LOIS2018-15, IE2018-35, EMM2018-54 
Volume (vol) vol.118 
Number (no) no.222(LOIS), no.223(IE), no.224(EMM) 
Page pp.29-30 
#Pages 2 
Date of Issue 2018-09-20 (LOIS, IE, EMM) 

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