A Study of Children Facial Recognition for Privacy in Smart TV

  • Patrick C. K. HungEmail author
  • Kamen Kanev
  • Farkhund Iqbal
  • David Mettrick
  • Laura Rafferty
  • Guan-Pu Pan
  • Shih-Chia Huang
  • Benjamin C. M. Fung
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10149)


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.


Smart TV Digital imaging Face recognition Picture-based age estimation Privacy 



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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Patrick C. K. Hung
    • 1
    • 2
    Email author
  • Kamen Kanev
    • 1
    • 3
    • 4
  • Farkhund Iqbal
    • 5
  • David Mettrick
    • 1
  • Laura Rafferty
    • 1
  • Guan-Pu Pan
    • 2
  • Shih-Chia Huang
    • 1
    • 2
  • Benjamin C. M. Fung
    • 6
  1. 1.Faculty of Business and Information TechnologyUniversity of Ontario Institute of TechnologyOshawaCanada
  2. 2.Department of Electronic EngineeringNational Taipei University of TechnologyTaipeiTaiwan
  3. 3.Graduate School of Science and TechnologyShizuoka UniversityHamamatsuJapan
  4. 4.Lassonde School of EngineeringYork UniversityTorontoCanada
  5. 5.College of Technological InnovationZayed UniversityDubaiUAE
  6. 6.School of Information StudiesMcGill UniversityMontrealCanada

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