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Rotation-invariant binary representation of sensor pattern noise for source-oriented image and video clustering
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Lin, Xufeng and Li, Chang-Tsun (2019) Rotation-invariant binary representation of sensor pattern noise for source-oriented image and video clustering. In: 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) , Auckland, New Zealand, 27-30 Nov 2018 . Published in: 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) pp. 1-6. ISBN 9781538692950. doi:10.1109/AVSS.2018.8639161
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Official URL: http://dx.doi.org/10.1109/AVSS.2018.8639161
Abstract
Most existing source-oriented image and video clustering algorithms based on sensor pattern noise (SPN) rely on the pairwise similarities, whose calculation usually dominates the overall computational time. The heavy computational burden is mainly incurred by the high dimensionality of SPN, which typically goes up to millions for delivering plausible clustering performance. This problem can be further aggravated by the uncertainty of the orientation of images or videos because the spatial correspondence between data with uncertain orientations needs to be reestablished in a brute-force search manner. In this work, we propose a rotation-invariant binary representation of SPN to address the issue of rotation and reduce the computational cost of calculating the pairwise similarities. Results on two public multimedia forensics databases have shown that the proposed approach is effective in overcoming the rotation issue and speeding up the calculation of pairwise SPN similarities for source-oriented image and video clustering.
Item Type: | Conference Item (Paper) | ||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
Library of Congress Subject Headings (LCSH): | Electronic surveillance, Signal processing -- Digital techniques, Image processing -- Digital techniques -- Mathematics, Closed-circuit television, Computer vision -- Mathematical models, Algorithms, Cluster analysis -- Data processing, Digital watermarking, Pattern perception | ||||||
Journal or Publication Title: | 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) | ||||||
Publisher: | IEEE | ||||||
ISBN: | 9781538692950 | ||||||
Book Title: | 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) | ||||||
Official Date: | 14 February 2019 | ||||||
Dates: |
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Page Range: | pp. 1-6 | ||||||
DOI: | 10.1109/AVSS.2018.8639161 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Reuse Statement (publisher, data, author rights): | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 15 May 2020 | ||||||
Date of first compliant Open Access: | 15 May 2020 | ||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | ||||||
Title of Event: | 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Auckland, New Zealand | ||||||
Date(s) of Event: | 27-30 Nov 2018 |
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