Abstract
Abstract As video surveillance systems are widely deployed, concerns continue to grow about invasion of privacy. We have built a privacy protected video surveillance system called PriSurv. Although PriSurv protects subject privacy using image processing, criteria of controlling the subject’s visual information that is privacy-sensitive should be clarified. Visual information must be disclosed by considering the trade-off between privacy and security. The level of privacy-sensitive visual information that could be disclosed to a viewer is simply called disclosable privacy in this chapter. Disclosable privacy, which deeply involves the personal sense, is affected by many factors. A sense of privacy is individual, but in some cases it might have common factors. A sense of privacy is individual, but in some cases it might have common factors. In this chapter, we analyze what factors determine and affect disclosable privacy by applying statistical analysis to questionnaire-based experimental results. These results indicate that disclosable privacy is concerned with how much a subject has feeling of closeness to a viewer and expects the viewer’s responsibility. They also show that disclosable privacy differs greatly by individuals. Reflecting the obtained findings in PriSurv’s design, we adapt PriSurv to reflect a personal sense of privacy.
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References
Babaguchi, N.: Video Surveillance Considering Privacy. In: IPSJ Magazine, Vol. 48, No. 1, pp. 30–36. (2007)
Bowyer, K.W.: Face Recognition Technology: Security Versus Privacy. In: IEEE Technology and Society Magazine, vol. 23, No. 1, pp. 9–19. (2004)
Boyle, M., Edwards, C., and Greenberg, S.: The Effects of Filtered Video on Awareness and Privacy. In: Proc. of CSCW’00, pp. 1–10, ACM Press. (2000)
Cavallaro, A., Steiger, O., and Ebrahimi, T.: Semantic Video Analysis for Adaptive Content Delivery and Automatic Description. In: IEEE Trans. Circuits and Systems for Video Technology, Vol. 15, No. 10, pp. 1200–1209. (2005)
Cass, S. and Riezenman, M.J.: Improving Security, Preserving Privacy. In: IEEE Spectrum, Vol. 39, No. 1, pp. 44–49. (2002)
Chang, Y., Yang, J., Chen, D., and Yan, R.:People Identification with Limited Labels in Privacy-Protected Video. In: Proc. of ICME2006. (2000)
Chinomi, K., Nitta, N., Ito, Y., and Babaguchi, N.: PriSurv: Privacy Protected Video Surveillance System Using Adaptive Visual Abstraction. In: Proc. 14th International Multimedia Modeling Conference, pp. 144–154. (2008)
Gross, R., Airoldi, E.M., Malin, B., and Sweeney, L.: Integrating Utility into Face De-identification. In: Proc. 5th Workshop on Privacy Enhancing Technologies, pp. 227–242. (2005)
Kaiser, H.K.: The Varimax Criterion for Analytic Rotation in Factor Analysis. In: Psychometrika, Vol. 23, 187–200. (1958)
Kitahara, I., Kogure, K., and Hagita, N.: Stealth Vision for Protecting Privacy. In: Proc. 17th International Conference on Pattern Recognition, Vol. 4, pp. 404–407. (2004)
Koshimizu, T., Toriyama, T., and Babaguchi, N.: Factors on the Sense of Privacy in Video Surveillance. In: Proc. 3rd ACM Workshop on Capture, Archival and Retrieval of Personal Experiences, pp. 35–43. (2006)
Koshimizu, T., Toriyama, T., Nishio, S., Babaguchi, N., and Hagita, N.: Visual Abstraction for Privacy Preserving Video Surveillance. In: Technical report of IEICE. PRMU, Vol. 2006, No. 25, pp. 247–252. (2006)
Langheinrich, M.: A Privacy Awareness System for Ubiquitous Computing Environments. In: Proc. 4th International Conference on Ubiquitous Computing, pp. 237–245. (2002)
Murakami, Y. and Murakami, C.: The Standardization of a Big Five Personality Inventory for Separate Generations. In: The Japanese Journal of Personality, Vol. 1, No. 8, pp. 32–42. (1999)
Murakami, Y. and Murakami, C.: Clinical Psychology Assessment Handbook, pp. 104–124, Kitaohji-Shobo. (2004)
Newton, E.M., Sweeney, L., and Malin, B.: Preserving Privacy by De-identifying Face Images. In: IEEE Trans. Knowledge and Data Engineering, Vol. 17, No. 2, pp. 232–243. (2005)
Sekiguchi, T. and Kato, H.: Proposal and Evaluation of Video-based Privacy Assuring System Based on the Relationship between Observers and Subjects (Development and Operation of Information Systems). In: Transactions of Information Processing Society of Japan, Vol. 47, No. 8, pp. 2660–2668. (2006)
Senior, A., Pankanti, S., Hampapur, A., Brown, L., Ying-Li Tian, Ekin, A., Connell, J., Chiao Fe Shu, and Lu, M.: Enabling Video Privacy Through Computer Vision. In: IEEE Security & Privacy Magazine, Vol. 3, No. 3, pp. 50–57. (2005)
Ward, J.H. and Hook, M. E.: Application of a Hierarchical Grouping Procedure to a Problem of Grouping Profiles. In: Educational and Psychological Measurement, Vol. 23, No. 1, pp. 69–82. (1963)
Wickramasuriya, J., Alhazzazi, M., Datt, M., Mehrotra, S., and Venkatasubramanian, N.: Privacy-protecting Video Surveillance. In: Proc. SPIE International Symposium on Electronic Imaging, Vol. 5671, pp. 64–75. (2005)
Zhang W., Cheung, S.S., and Chen, M.: Hiding Privacy Information in Video Surveillance System. In: IEEE International Conference on Image Processing, pp. 868–871. (2005)
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Babaguchi, N., Koshimizu, T., Umata, I., Toriyama, T. (2009). Psychological Study for Designing Privacy Protected Video Surveillance System: PriSurv. In: Senior, A. (eds) Protecting Privacy in Video Surveillance. Springer, London. https://doi.org/10.1007/978-1-84882-301-3_9
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DOI: https://doi.org/10.1007/978-1-84882-301-3_9
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