DOI QR코드

DOI QR Code

Development of Multimedia Content Usage Analysis Service Platform Utilizing Attention and Understanding Flows

멀티미디어 콘텐츠 응시와 이해도 기반 분석 서비스 플랫폼 기술

  • 고기남 (호서대학교 벤처전문대학원 융합공학과) ;
  • 문남미 (호서대학교 모바일소프트웨어학과)
  • Received : 2015.02.02
  • Accepted : 2015.07.27
  • Published : 2015.08.31

Abstract

The purposed of this research is to develop multimedia content usage analysis service platform. In the proposed platform, the content gazing behaviors of the users are monitored and profiled in real-time and a set of quantifiable metrics is provided. These metrics are used to determine the closeness of the users' behavior from the intent set by the provider. Based on the evaluation, it is possible to assess the effectiveness of the contents themselves as well. The content usage assessment is accomplished by utilizing the intention flow and the intent weight, which are embedded into the content by the content provider. Proposed methodology can be effectively applied and used in various application domains such as in education and in commercial advertisements.

본 연구의 목적은 시선 관심 객체 기반 양방향 서비스를 효율적으로 하기 위해, 멀티미디어 콘텐츠를 시청하는 소비자의 응시 행위를 개별 객체 중심으로 실시간 모니터링하고, 콘텐츠 소비 시점의 맥락적 소비자 이해도를 인지하여 콘텐츠 제공의도에 맞는 소비행태 분석을 제공하는 플랫폼 기술을 제공하는 데 있다. 이를 위해 미디어 콘텐츠 내 개별 객체 표현 구조를 연구하고, 미디어 제공자의 의도와 비교하여 제공자가 의도한 계획에 맞춰 소비되고 있는지를 파악할 수 있도록 한다. 소비자의 소비행태 분석은 응시 분석(Gaze Profile Analysis)과 콘텐츠 제공자에 의해 제공된 의도 흐름(Intention Flow)과 가중치(Intention Weight)를 분석한 정보를 사용하여 이루어진다. 이와 같은 기술은 교육, 광고 등에 효과적으로 사용될 수 있을 것으로 기대된다.

Keywords

References

  1. "Eye Tracking Technology Trend and Utilization", Technology Hot Issues, 2010.
  2. Jeong Ho Lee, Ji Hun Kim, and Young Shik Moon, "Multi-Object Detection Using Image Segmentation and Salient Points," Journal of The Institute of Electronics Engineers of Korea, Vol.45, No.2, 2008.
  3. Sun Do Kang, "Content-Based Image Retrieval Using Extracted Object Feature," Korea University, 2009.
  4. Asier Lopez-Basterretxea, et al, "Eye/head Tracking Technology to Improve HCI with iPad Applications", Sensors 2015, Vol.15, No.2, pp.2244-2264, 2015.
  5. [Internet] http://searchengineland.com/new-google-eyetracking-study-shows-downfall-golden-triangle-205274.
  6. Marco Porta, "A Study on Text Entry Methods Based on Eye Gestures," Journal of Assistive Technologies, Vol.9, Issue.5, 2007.
  7. H. W. Jung, J. S. Lee, and Y. H. Suh, "Research Trend of Illegal Contents Trace Technology," Electronics and Telecommunications Trends, Vol.20, No.4, 2005.
  8. [Internet] https://itec.etri.re.kr/itec/sub02/sub02_01_1.do.
  9. Xiaohui Shen, et al, "Mobile Product Image Search by Automatic Query Object Extraction", ECCV 2012, Part IV, LNCS 7575, pp.114-127, 2012.
  10. A. P. Bodkhe, "A Literature Review on Different models for Human and Vehicle Tracking," International Journal of Innovative Research in Computer and Communication Engineering, Vol.3, Issue.5, 2015.
  11. [Internet] http://www.bloter.net/archives/124915
  12. Khairil Imran Bin Ghaute and Nor Aniza Abdullah, "Building an E-Learning Recommender System using Vector Space Model and Good Learners Average Rating," 2009 Ninth IEEE International Conference on Advanced Learning Technologies, 2009.
  13. Won-Ik Park, Woo-Je Shim, and Young-Kuk Kim, "A Mobile Multimedia Contents Recommendation Technique Considering Users' Psychological Patterns and Situations", Journal of KIISE, Vol.16, No.2, 2010.
  14. C. H. Ahn, J. H. Choi, S. J. Yang, W. T. Lim, and J. H. Cha, "Trends of Emotional Information Service," Electronics and Telecommunications Trends, 2012.
  15. [Internet] http://www.dtalker.net/www/News/NewsView.php?p_grpcode=A&p_brdcode=05&p_seq=3721.
  16. Adam Rae, Borkur Sigubjornsson, and Roelof van Zwol, "Improving Tag Recommendation using Social Networks", Proceeding RIAO'10 Adaptivity, pp.92-99, 2010.
  17. Dongjoo Lee, Sang-keun Lee, and Sang-goo Lee, "Considering temporal context in music recommendation based on collaborative filtering," Korea Computer Congress 2009, Vol.36, No.1, pp.123-128, 2009.
  18. [Internet] http://www.tobii.com/eye-tracking-integration/global/eye-tracking.
  19. [Internet] http://www.eyetracking.co.kr.
  20. Tae Yeun Kim, Byoung Ho Song, and Sang Hyun Bae, "A Design and Implementation of Music & Image Retrieval Recommendation System based on Emotion," Journal of The Instituute of Electronics Engineers of Korea CI, Vol.47, No.1, 2010.
  21. Hadi Hadizadeh, et al., "Eye-Tracking Database for a Set of Standard Video Sequences," IEEE Transactions on Image Processing, 2012.
  22. Markus Huff, et al, "Eye movements across viewpoint changes in multiple object tracking," Visual Cognition, 2010.
  23. Tie Liu, et al., "Learning to Detect a Salient Object," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011.
  24. Edward Vul, et al, "Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model," Advances in Neural, 2009.
  25. Y. S. Akgul, "Eye-gaze based real-time surveillance video synopsis," U. Vural, Pattern Recognition Letters, Vol.30, Issue 12, Sep., 2009.