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Paper Abstract and Keywords
Presentation 2019-03-13 15:15
[Poster Presentation] A Consideration on Spatio-Temporal Feature Learning for Video Forgery Detection
Shoken Ohshiro (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2018-104
Abstract (in Japanese) (See Japanese page) 
(in English) The purpose of our work is to detect objects tampered in the spatial domain of videos including dynamic scenes such as a video taken with a smartphone. We use forgery detection models based on spatio-temporal Convolutional Neural Networks (CNN) to consider spatial and temporal aspects of videos. In this paper, we adopt (2+1)D CNN, which is one of the CNNs and calculates each convolution individually. We investigate the influences of spatial and temporal features on video forgery detection. We also report that our proposed forgery detection system based on (2+1)D CNN achieved higher accuracy than a detection system based on 3D CNN.
Keyword (in Japanese) (See Japanese page) 
(in English) Video Analysis / Video Forgery Detection / Passive Approach / Spatio-Temporal Convolutional Neural Network / Object Modification / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 494, EMM2018-104, pp. 67-72, March 2019.
Paper # EMM2018-104 
Date of Issue 2019-03-06 (EMM) 
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)
Download PDF EMM2018-104

Conference Information
Committee EMM  
Conference Date 2019-03-13 - 2019-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English) TBD 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image and Sound Quality, Metrics for Perception and Recognition, Human Auditory and Visual System, etc. 
Paper Information
Registration To EMM 
Conference Code 2019-03-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Consideration on Spatio-Temporal Feature Learning for Video Forgery Detection 
Sub Title (in English)  
Keyword(1) Video Analysis  
Keyword(2) Video Forgery Detection  
Keyword(3) Passive Approach  
Keyword(4) Spatio-Temporal Convolutional Neural Network  
Keyword(5) Object Modification  
1st Author's Name Shoken Ohshiro  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Kazuhiro Kono  
2nd Author's Affiliation Kansai University (Kansai Univ.)
3rd Author's Name Noboru Babaguchi  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Date Time 2019-03-13 15:15:00 
Presentation Time 60 
Registration for EMM 
Paper # IEICE-EMM2018-104 
Volume (vol) IEICE-118 
Number (no) no.494 
Page pp.67-72 
#Pages IEICE-6 
Date of Issue IEICE-EMM-2019-03-06 

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