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Paper Abstract and Keywords
Presentation 2018-10-19 09:30
Perceptual Quality Driven Adaptive Video Coding for VOD Streaming
Yusuke Sakamoto, Masaru Takeuchi, Shintaro Saika, Tatsuya Nagashima, Zhengxue Cheng, Kenji Kanai, Jiro Katto (Waseda Univ.), Kaijin Wei, Ju Zengwei, Xu Wei (Huawei Technologies) IE2018-44
Abstract (in Japanese) (See Japanese page) 
(in English) In video streaming on the Internet, getting a good encoding recipe (i.e. bitrate-resolution pairs) is a main problem to deliver the highest quality video streams. By using multiple bitrate/resolution encoding like MPEG-DASH, video streaming services can deliver the best video stream to a client, under the conditions of the client’s available bandwidth and viewing device capability. However, conventional fixed encoding recipes (i.e. resolution-bitrate pairs) suffer from many problems, such as improper resolution selection and stream redundancy. To avoid these problems, we propose a novel video coding method, which generates multiple representations with constant Just-Noticeable Difference (JND) interval, using a JND scale estimator which we developed with Support Vector Regression (SVR). Experimental results confirm that our proposed method can achieve better rate-JND characteristics than conventional fixed recipe.
Keyword (in Japanese) (See Japanese page) 
(in English) Adaptive Video Coding / Just-Noticeable Difference / Perceptual Video Quality / Machine Learning / MPEG-DASH / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 259, IE2018-44, pp. 1-6, Oct. 2018.
Paper # IE2018-44 
Date of Issue 2018-10-12 (IE) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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)
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Conference Information
Committee IE ITE-ME ITE-AIT  
Conference Date 2018-10-19 - 2018-10-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2018-10-IE-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Perceptual Quality Driven Adaptive Video Coding for VOD Streaming 
Sub Title (in English)  
Keyword(1) Adaptive Video Coding  
Keyword(2) Just-Noticeable Difference  
Keyword(3) Perceptual Video Quality  
Keyword(4) Machine Learning  
Keyword(5) MPEG-DASH  
1st Author's Name Yusuke Sakamoto  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Masaru Takeuchi  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Shintaro Saika  
3rd Author's Affiliation Waseda University (Waseda Univ.)
4th Author's Name Tatsuya Nagashima  
4th Author's Affiliation Waseda University (Waseda Univ.)
5th Author's Name Zhengxue Cheng  
5th Author's Affiliation Waseda University (Waseda Univ.)
6th Author's Name Kenji Kanai  
6th Author's Affiliation Waseda University (Waseda Univ.)
7th Author's Name Jiro Katto  
7th Author's Affiliation Waseda University (Waseda Univ.)
8th Author's Name Kaijin Wei  
8th Author's Affiliation Huawei Technologies Co. Ltd. (Huawei Technologies)
9th Author's Name Ju Zengwei  
9th Author's Affiliation Huawei Technologies Co. Ltd. (Huawei Technologies)
10th Author's Name Xu Wei  
10th Author's Affiliation Huawei Technologies Co. Ltd. (Huawei Technologies)
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Speaker Author-1 
Date Time 2018-10-19 09:30:00 
Presentation Time 30 minutes 
Registration for IE 
Paper # IE2018-44 
Volume (vol) vol.118 
Number (no) no.259 
Page pp.1-6 
Date of Issue 2018-10-12 (IE) 

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