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OTT user authentication system by age classification

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Abstract

The number and types of channels and programs that viewers can choose have been explosively increased since the digital broadcasting service was provided to almost every household while the ground wave broadcastings have been stayed. Since sexual, violent, and antisocial contents have been rapidly it increased to competition broadcasting. The primary goal of this study is to develop a system to restrict viewing of adolescents for improper broadcasting linking with the contents DB system inside OTT device. For the purpose an algorithm to detect the age of viewers of OTT broadcasting is proposed.

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References

  1. Isobe, T., Fujiwara, M.H.: Development and features of a TV navigation system. IEEE Trans. Consum. Electron. 49(4), 393–399 (2003)

    Article  Google Scholar 

  2. Koh, S.H.: A software architecture life cycle model based on the program management perspective: the expanded spiral model. J. Inform. Technol. Appl. Manag. 20(2), 69–87 (2013)

    Google Scholar 

  3. Woo, H.J., Dominick, J.R.: Acculturation, cultivation, and daytime TV talk shows. J. Mass Commun. Quart. 80(1), 109–127 (2003)

    Google Scholar 

  4. Choi, S.: TV audience flow and channel dynamics: analysis of audience duplication with panel data of 2009 and 2012. Korean J. Broadcast. Telecommun. Stud. 27(5), 39–56 (2013)

    Google Scholar 

  5. Papageorgiou, C.P., Oren, M., Poggio, T.: A General Framework for Object Detection. In: Proceedings of 6th IEEE 48 International Conference on Computer Vision, pp. 555–562 (1998)

  6. Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comp. Vision 57(2), 137–154 (2004)

    Article  Google Scholar 

  7. Chin, R.T., Harlow, C.A.: Automated visual inspection: a survey. IEEE Trans. Pat. Anal. Mach. Intel. 4(6), 1–46 (1982)

    Google Scholar 

  8. Sprague, A.P., Donahue, M.J., Rokhlim, S.I.: A method for automated inspection of printed circuit boards. Image Understand. 54(3), 401–415 (1991)

    Article  MATH  Google Scholar 

  9. Young Ho, K., Lobo, N,D.: Age classification from facial images. Proc. Int. Conf. Comp. Vision Pat. Recogn. 74(1), 1–21 (1994)

    Google Scholar 

  10. Hongtao, S., Feng, D.D., Rong-Chun, Z.: Face recognition using multi-feature and radial basis function network. Conf. Res. Pract. Inform. Technol. 22, 51–57 (2003)

    Google Scholar 

  11. Ming-Hsuan, Y., Kriegman, D.J., Ahuja, N.: Detecting faces in images: a survey. Trans. Pat. Anal. Mach. Intel. 24(1), 34–58 (2002)

    Article  Google Scholar 

  12. Geng, X., Zhi-Hua, Z., Smith-Miles, K.: Automatic age estimation based on facial aging patterns. IEEE Trans. Pat. Anal. Mach. Intel. 29(12), 2234–2240 (2007)

    Article  Google Scholar 

  13. Suo, J., Wu, J., Zhu, T., Shan, S., Chen, X., Gao, X.: Design Sparse Features for Age Estimation using Hierarchical Face Model. In: 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG ’08. pp 1–6 (2008)

  14. Minear, M., Park, D.C.: A lifespan database of adult facial stimuli. Behav. Res. Methods Instrum. Comp. 36(4), 630–633 (2004)

  15. Sichitiu, M.L., Kihl, M.: Inter-vehicle communication systems: a survey. Proc IEEE Commun. Surveys Tutorials 10(2), 88–105 (2008)

    Article  Google Scholar 

  16. Biswas, S., Tatchikou, R., Dion, F.: Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety. Proc. IEEE Commun. Mag. 44(1), 74–82 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

The work of Kiyoug, Kim, Byung-Joon, Park, Yuhwa, Suh, and Jaepyo, Park was supported by the Small Business Administration (Academic Industrial collaborative technology development project. No.C0237831).

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Authors and Affiliations

  1. Department of Computer Software, Seoil University, Seoul, 131-702, Republic of Korea

    Ki-young Kim & Byung-Joon Park

  2. Department of Computer Science and Engineering, Soongsil University, Seoul, 156-743, South Korea

    Yuhwa Suh

  3. Graduate school of Information Science, Soongsil University, Seoul, 156-743, South Korea

    Jaepyo Park

Authors
  1. Ki-young Kim
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  2. Byung-Joon Park
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  3. Yuhwa Suh
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  4. Jaepyo Park
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Correspondence to Byung-Joon Park.

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Kim, Ky., Park, BJ., Suh, Y. et al. OTT user authentication system by age classification. J Comput Virol Hack Tech 12, 169–175 (2016). https://doi.org/10.1007/s11416-016-0268-0

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  • DOI: https://doi.org/10.1007/s11416-016-0268-0

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