Abstract
Nowadays Smart TV is becoming very popular in many families. Smart TV provides computing and connectivity capabilities with access to online services, such as video on demand, online games, and even sports and healthcare activities. For example, Google Smart TV, which is based on Google Android, integrates into the users’ daily physical activities through its ability to extract and access context information dependent on the surrounding environment and to react accordingly via built-in camera and sensors. Without a viable privacy protection system in place, however, the expanding use of Smart TV can lead to privacy violations through tracking and user profiling by broadcasters and others. This becomes of particular concern when underage users such as children who may not fully understand the concept of privacy are involved in using the Smart TV services. In this study, we consider digital imaging and ways to identify and properly tag pictures of children in order to prevent unwanted disclosure of personal information. We have conducted a preliminary experiment on the effectiveness of facial recognition technology in Smart TV where experimental recognition of child face presence in feedback image streams is conducted through the Microsoft’s Face Application Programming Interface.
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Anggraini, D.R.: Face recognition using principal component analysis and self organizing maps. In: Proceedings of 2014 Third ICT International Student Project Conference (ICT-ISPC), pp. 91–94 (2014)
Government of Canada: Personal Information Protection and Electronic Documents Act. http://laws-lois.justice.gc.ca/eng/acts/P-8.6/
Canadian Standards Association: Archived - Appendix 3: Model Code for the Protection of Personal Information (1996). http://cmcweb.ca/epic/internet/incmc-cmc.nsf/en/fe00076e.html
Chakraborty, S., Raghavan, K.R., Johnson, M.P., Srivastava, M.B.: A framework for context-aware privacy of sensor data on mobile systems. In: Proceedings of Fourteenth Workshop on Mobile Computing Systems and Applications (ACM HotMobile 2013), New York (2013)
Cherubini, M., de Oliveira, R., Hiltunen A., Oliver, N.: Barriers and bridges in the adoption of today’s mobile phone contextual services. In: Proceedings of 13th International Conference on Human Computer Interaction with Mobile Devices and Services (MobileHCI 2011), pp. 167–176, Stockholm (2011)
Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., Morris, J., Hansen, M., Smith, R.: RFC 6973: Privacy Considerations for Internet Protocols. IETF (2013)
Dewri, R., Annadata, P., Eltarjaman, W., Thurimella, R.: Inferring trip destinations from driving habits data. In: Workshop on Privacy in the Electronic Society, Berlin (2013)
Enck, W., Ongtang, M., McDaniel, P.: Understanding android security. IEEE Secur. Priv. 7(1), 50–57 (2009)
WIPO: Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data. http://www.wipo.int/wipolex/en/details.jsp?id=13580
GSMA: User Perspectives on Mobile Privacy - Summary of Research Findings (2011). http://www.gsma.com/publicpolicy/wp-content/uploads/2012/03/futuresightuserperspectivesonuserprivacy.pdf
Ghiglieri, M.: I know what you watched last Sunday: a new survey of privacy in HbbTV. In: Workshop of Web 2.0 Security and Privacy 2014 in Conjunction with the IEEE Symposium on Security and Privacy (2014)
Ghiglieri, M., Tews, E.: A privacy protection system for HbbTV in Smart TVs. In: IEEE 11th Consumer Communications and Networking Conference (CCNC), pp. 648–653 (2014)
Government of Canada: Schedule 1 (Section 5) Principles Set out in the National Standard of Canada Entitled Model Code for the Protection of Personal Information, Personal Information Protection and Electronic Act (PIPEDA) (2000)
Horiuchi, T., Hada, T.: A complementary study for the evaluation of face recognition technology. In: Proceedings of 47th International Carnahan Conference on Security Technology (ICCST) (2013)
Huang, Y.S., Chen, S.Y.: A geometrical-model-based face recognition. In: Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 3106–3110 (2015)
Hung, P.C.K., Cheng, V.S.Y.: Privacy and trust. In: Liu, L., Tamer Özsu, M. (eds.) Encyclopedia of Database Systems, pp. 2136–2137. Springer, New York (2009)
Landau, S.: What was Samsung thinking? IEEE Secur. Priv. 13(3), 3–4 (2015)
Lee, S.H., Sohn, M.K., Kim, D.J., Kim, B., Kim, H.: Smart TV interaction system using face and hand gesture recognition. In: Proceedings of 2013 IEEE International Conference on Consumer Electronics (ICCE), pp. 173–174 (2013)
MEF Global Privacy Report 2013, MEF (2013)
Microsoft Cognitive Services: Face API. https://www.microsoft.com/cognitive-services/en-us/face-api
Nguyen, D.T., Shin, K.Y., Lee, W.O., Oh, C., Lee, H., Jeong, Y.: Gaze detection based on head pose estimation in Smart TV. In: Proceedings of 2013 International Conference on Information and Communication Technology Convergence (ICTC), pp. 283–288 (2013)
OCED: The OECD Privacy Framework. http://www.oecd.org/sti/ieconomy/oecd_privacy_framework.pdf
Ragashe, M.U., Goswami, M.M., Raghuwanshi, M.M.: Approach towards real time face recognition in streaming video under partial occlusion. In: Proceedings of 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO) (2015)
Saha, D.: Pervasive computing: a paradigm for the 21st century. IEEE Comput. 36(3), 25–31 (2003)
Salomon, D.: Privacy and trust. In: Salomon, D. (ed.) Elements of Computer Security. Undergraduate Topics in Computer Science, pp. 273–290. Springer, London (2010)
Schmidt, A.: Interactive context-aware systems interacting with ambient intelligence. In: Riva, G., Vatalaro, F., Davide, F., Alcaniz, M. (eds.) Ambient Intelligence, pp. 159–178. IOS Press, Amsterdam (2005)
Shabtai, A., Fledel, Y., Kanonov, U., Glezer, C.: Google Android: a comprehensive security assessment. IEEE Secur. Priv. 8(2), 35–44 (2010)
Soldera, J., Behaine, C.A.R., Scharcanski, J.: Customized orthogonal locality preserving projections with soft-margin maximization for face recognition. IEEE Trans. Instrum. Meas. 64(9), 2417–2426 (2015)
United States Federal Trade Commission: Children’s Online Privacy Protection Act of 1998. http://www.coppa.org/coppa.htm
World Economic Forum: Personal Data: The Emergence of a New Asset Class (2011). http://www3.weforum.org/docs/WEF_ITTC_PersonalDataNewAsset_Report_2011.pdf
Xi, M., Chen, L., Polajnar, D., Tong, W.: Local binary pattern network: a deep learning approach for face recognition. In: Proceedings of 2016 IEEE International Conference on Image Processing (ICIP), pp. 3224–3228 (2016)
Yusufov, M., Paramonov, I., Timofeev, I.: Medicine tracker for Smart TV. In: Proceedings of 14th Conference of Open Innovations Association (FRUCT), pp. 164–170 (2013)
Acknowledgements
This work was supported by the Ministry of Science and Technology (MOST), Taiwan under MOST Grants: 105-2923-E-002-014-MY3, 105-2923-E-027-001-MY3, 105-2221-E-027-113, and 105-2811-E-027-001; the Research Office- Zayed University, Abu Dhabi, United Arab Emirates under Research Projects: R15048 and R16083; the Natural Sciences and Engineering Research Council of Canada (NSERC) under Discovery Grants Program: RGPIN-2016-05023; and the 2016 Cooperative Research Project at Research Center of Biomedical Engineering with RIE Shizuoka University.
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Hung, P.C.K. et al. (2017). A Study of Children Facial Recognition for Privacy in Smart TV. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2016. Lecture Notes in Computer Science(), vol 10149. Springer, Cham. https://doi.org/10.1007/978-3-319-54609-4_17
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