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research-article

Privacy perception and fall detection accuracy for in-home video assistive monitoring with privacy enhancements

Published: 01 September 2012 Publication History

Abstract

Video of in-home activity provides valuable information for assistive monitoring but raises privacy concerns. Raw video can be privacy-enhanced by obscuring the appearance of a person. We consider five privacy enhancements: blur, silhouette, oval, box, and trailing-arrows. We investigate whether a privacy enhancement exists that provides sufficient perceived privacy while enabling accurate fall detection by humans. We recorded 23 1-minute videos involving normal household activities, falling, and lying on the floor after an earlier fall, and created versions of each video for each privacy setting. We conducted an experiment with 376 undergraduate, non-engineering student participants to measure perceived privacy protection and the participant's fall detection accuracy for each privacy setting. Results indicate that the oval provides sufficient perceived privacy for 88% of participants while still supporting fall detection accuracy of 89%, and that the common privacy enhancements blur and silhouette were perceived to provide insufficient privacy.

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Cited By

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  • (2023)Do Streamers Care about Bystanders' Privacy? An Examination of Live Streamers' Considerations and Strategies for Bystanders' Privacy ManagementProceedings of the ACM on Human-Computer Interaction10.1145/35796037:CSCW1(1-29)Online publication date: 16-Apr-2023
  • (2023)Privacy-Preserved Video Monitoring Method with 3D Human Pose Estimation2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD57460.2023.10152735(1502-1507)Online publication date: 24-May-2023
  • (2020)Elderly Fall Detection Systems: A Literature SurveyFrontiers in Robotics and AI10.3389/frobt.2020.000717Online publication date: 23-Jun-2020
  • Show More Cited By

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Information

Published In

cover image ACM SIGHIT Record
ACM SIGHIT Record  Volume 2, Issue 2
September 2012
48 pages
EISSN:2158-8813
DOI:10.1145/2384556
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2012
Published in SIGHIT Volume 2, Issue 2

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Author Tags

  1. assistive monitoring
  2. privacy
  3. privacy-enhanced video
  4. smart home
  5. video

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Cited By

View all
  • (2023)Do Streamers Care about Bystanders' Privacy? An Examination of Live Streamers' Considerations and Strategies for Bystanders' Privacy ManagementProceedings of the ACM on Human-Computer Interaction10.1145/35796037:CSCW1(1-29)Online publication date: 16-Apr-2023
  • (2023)Privacy-Preserved Video Monitoring Method with 3D Human Pose Estimation2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD57460.2023.10152735(1502-1507)Online publication date: 24-May-2023
  • (2020)Elderly Fall Detection Systems: A Literature SurveyFrontiers in Robotics and AI10.3389/frobt.2020.000717Online publication date: 23-Jun-2020
  • (2020)Modeling Temporal Visual Salience for Human Action Recognition Enabled Visual Anonymity PreservationIEEE Access10.1109/ACCESS.2020.30397408(213806-213824)Online publication date: 2020
  • (2018)An Autonomous Architecture that Protects the Right to PrivacyProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society10.1145/3278721.3278768(330-334)Online publication date: 27-Dec-2018
  • (2018)Privacy-preserving Image Processing with Binocular Thermal CamerasProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/31611981:4(1-25)Online publication date: 8-Jan-2018
  • (2017)Blur vs. Block: Investigating the Effectiveness of Privacy-Enhancing Obfuscation for Images2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW.2017.176(1343-1351)Online publication date: Jul-2017
  • (2017)Efficient fall detection based on event pattern matching in image streams2017 IEEE International Conference on Big Data and Smart Computing (BigComp)10.1109/BIGCOMP.2017.7881715(51-58)Online publication date: Feb-2017
  • (2016)A Vision-Based Approach for Building Telecare and Telerehabilitation ServicesSensors10.3390/s1610172416:10(1724)Online publication date: 18-Oct-2016
  • (2015)Visual privacy protection methodsExpert Systems with Applications: An International Journal10.1016/j.eswa.2015.01.04142:9(4177-4195)Online publication date: 1-Jun-2015
  • Show More Cited By

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