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Automatically protecting privacy in consumer generated videos using intended human object detector

Published: 25 October 2010 Publication History

Abstract

The growing popularity of video sharing services such as YouTube enables us to upload and share consumer generated videos (CGVs) easily, resulting in disclosure of the privacy sensitive information (PSI) of persons, i.e., their appearances. Therefore, we need a technique for automatically protecting the privacy in CGVs; however, the main problem is how to determine PSI regions automatically. In this paper, we propose a novel system for automatically protecting the privacy in CGVs. The proposed system tackles the problem of determining PSI regions by using an intended human object detector that detects human objects which the camera person wanted to capture to achieve his/her capture intention. In addition, the proposed system adopts several PSI obscuring methods such as blocking out, blurring and seam carving. We present the results of subjective evaluations of a privacy protected video in terms of the visual quality and acceptability of PSI disclosure, as well as the performance of the intended human object detector.

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  • (2023)Pri-EMO: A Universal Perturbation Method for Privacy Preserving Facial Emotion RecognitionJournal of Information and Intelligence10.1016/j.jiixd.2023.08.001Online publication date: Aug-2023
  • (2018)Anonymous subject identification and privacy information management in video surveillanceInternational Journal of Information Security10.1007/s10207-017-0380-217:3(261-278)Online publication date: 1-Jun-2018
  • (2016)Privacy Protection for Social Video via Background Estimation and CRF-Based Videographer's Intention ModelingIEICE Transactions on Information and Systems10.1587/transinf.2015EDP7378E99.D:4(1221-1233)Online publication date: 2016
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    cover image ACM Conferences
    MM '10: Proceedings of the 18th ACM international conference on Multimedia
    October 2010
    1836 pages
    ISBN:9781605589336
    DOI:10.1145/1873951
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 25 October 2010

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    Author Tags

    1. consumer generated videos
    2. intended human object detector
    3. privacy protection

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    MM '10
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    MM '10: ACM Multimedia Conference
    October 25 - 29, 2010
    Firenze, Italy

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    Overall Acceptance Rate 554 of 2,551 submissions, 22%

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    Cited By

    View all
    • (2023)Pri-EMO: A Universal Perturbation Method for Privacy Preserving Facial Emotion RecognitionJournal of Information and Intelligence10.1016/j.jiixd.2023.08.001Online publication date: Aug-2023
    • (2018)Anonymous subject identification and privacy information management in video surveillanceInternational Journal of Information Security10.1007/s10207-017-0380-217:3(261-278)Online publication date: 1-Jun-2018
    • (2016)Privacy Protection for Social Video via Background Estimation and CRF-Based Videographer's Intention ModelingIEICE Transactions on Information and Systems10.1587/transinf.2015EDP7378E99.D:4(1221-1233)Online publication date: 2016
    • (2016)Evaluating Protection Capability for Visual Privacy InformationIEEE Security and Privacy10.1109/MSP.2016.314:1(55-61)Online publication date: 1-Jan-2016
    • (2015)Protection and Utilization of Privacy Information via SensingIEICE Transactions on Information and Systems10.1587/transinf.2014MUI0001E98.D:1(2-9)Online publication date: 2015
    • (2015)Facial expression preserving privacy protection using image melding2015 IEEE International Conference on Multimedia and Expo (ICME)10.1109/ICME.2015.7177394(1-6)Online publication date: Jun-2015
    • (2014)Selective Concealment of Characters for Privacy Protection2014 22nd International Conference on Pattern Recognition10.1109/ICPR.2014.66(333-338)Online publication date: Aug-2014
    • (2013)Real-time privacy protection system for social videos using intentionally-captured persons detection2013 IEEE International Conference on Multimedia and Expo (ICME)10.1109/ICME.2013.6607622(1-6)Online publication date: Jul-2013
    • (2013)Inferring what the videographer wanted to capture2013 IEEE International Conference on Image Processing10.1109/ICIP.2013.6738040(191-195)Online publication date: Sep-2013
    • (2011)Extracting intentionally captured regions using point trajectoriesProceedings of the 19th ACM international conference on Multimedia10.1145/2072298.2072029(1417-1420)Online publication date: 28-Nov-2011
    • Show More Cited By

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