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    Title: 智慧型互動電視之實驗平台的設計-SITV
    An Experimental Platform for Smart Interactive TV-SITV
    Authors: 劉炳億
    Liu, Ping-Yi
    Contributors: 李蔡彥
    Li, Tsai-Yen
    劉炳億
    Liu, Ping-Yi
    Keywords: 互動電視
    模擬電視平台
    電視新功能
    電視觀看行為
    Interactive TV
    Emulated TV
    New TV Function
    TV Watching Behaviors
    Date: 2007
    Issue Date: 2009-09-17 14:05:21 (UTC+8)
    Abstract: 近年來,智慧型互動電視是不少數位生活研究的焦點。我們認為,一個好的互動電視系統設計,必須了解使用者觀看電視時的行為與周遭情境。因此,在本研究中,我們以Windows Media Center為基礎,提出一套互動電視的實驗平台系統─「SITV」,希望可輔助我們找出使用者在觀看電視時的行為特徵以及主觀上的需求反應。在SITV上,實驗設計者可以模擬一般有線電視節目的瀏覽方式,安排頻道順序與節目流程,定義電視上的功能,收集使用者的操作資訊,以及整合其他外部應用系統。我們亦設計了幾個實驗來評估我們所設計的電視新功能之效用性,包括新的音量控制方式,快速地檢視最近觀看過的頻道,個人化的節目推薦功能以及幾個具情境感知的應用規則(以電腦視覺技術為主)。我們相信SITV將作為一個創新的實驗平台,可以使得智慧型互動電視的設計更為容易。我們也將持續的進行更多的心理實驗來了解使用者的行為,以及如何設計出有用的電視新功能。
    Smart interactive TV has been the focus of much research on digital life in recent years. We regard that a good design for interactive TV should be based on better understanding of user behaviors and viewing contexts in TV watching. Therefore, in this research, on top of the Windows Media Center, we propose to build an experimental platform called Smart Interactive TV (SITV) to help us find out the characteristics of user behavior and subjective needs when watching the kind of TV. On SITV, designers are allowed to emulate broadcasting programs, schedule the programs, define control functions, collect user interaction data, and incorporate external application systems. We have designed several experiments to evaluate the effectiveness of our new context-aware control functions including volume control, fast retrieval of newly viewed programs, personalized program recommendation, and rule-based context-aware functions by the use of computer vision techniques. We believe that SITV will serve as a novel experiment platform to facilitate the design of smart interactive TV. We will continue to conduct more psychological experiments to better understand user behaviors and how to design effective functions on this kind of TV environment.
    Reference: [1] B. P. Bradley, M. Garner, L. Hudson and K. Mogg, “Influence of negative affect on selective attention to smoking-related cues and urge to smoke in cigarette smokers” Behavioural Pharmacology, 18(4):255-263, 2007.
    [2] Y. Blanco-Fernandez, J.J. Pazos-Arias, A. Gil-Solla, M. Ramos-Cabrer, B. Barragans-Martinez, and M. Lopez-Nores, “A Multi-Agent Open Architecture for a TV Recommender System: A Case Study using a Bayesian Strategy,” in Proc. of IEEE Sixth International Symposium on Multimedia Software Engineering, 2004.
    [3] Y. Blanco-Fernandez, J.J. Pazos-Arias, A. Gil-Solla, M. Ramos-Cabrer, M. Lopez-Nores and B. Barragans-Martinez, ”AVATAR: Modeling Users by Dynamic Ontologies in a TV Recommender System based on Semantic Reasoning,” in Proc. of the 3rd EuroITV Conference, 2005.
    [4] E.M.A. Diederiks, ”Buddies in a Box - Animated Characters in Consumer Electronics,” in Proc. of the 8th international conference on Intelligent user interfaces, pp. 34-38, 2003.
    [5] M.J. Darnell, ”How Do People Really Interact With TV? Naturalistic Observations of Digital TV and Digital Video Recorder Users,” in Proc. of ACM Computers in Entertainment, Vol. 5, 2007.
    [6] L. Eronen, ”Combining Quantitative and Qualitative Data in User Research on Digital Television,” in Proc. of the 1st Panhellenic Conference with International Participation on Human-Computer Interaction, pp. 51-56, 2001.
    [7] Y. Hara, Y. Tomomune and M. Shigemori, “Categorization of Japanese TV Viewers Based on Program Genres They Watch,” in Proc. of User Modeling and User-Adapted Interaction, 14(1):87-117, 2004.
    [8] J.B.D.S. Jr., R. Goularte, G.B. Faria and E.D.S. Moreira, ”Modeling of User Interaction in Context-Aware Interactive Television Application on Distributed,” in Proc. of Workshop on Personalization in Future TV, 2001.
    [9] J. Kallenbach, S. Narhi and P. Oittinen, ”Effects of Extra Information on TV Viewers’ Visual Attention, Message Processing Ability, and Cognitive Workload,” in Proc. of ACM Computers in Entertainment, Vol. 5, 2007.
    [10] B. Ludwig, S. Mandl and S.V. Mammen, ”What’s on tonight - User-centered and Situation-aware Proposals for TV Programmes,” in Proc. of International Conference on Intelligent User Interfaces, pp. 258-260, 2006.
    [11] C-H J. Lee, C. Chang, H. Chung, C. Dickie and T. Selker, ”Emotionally Reactive Television,” in Proc. of Intelligent User Interface, 2007.
    [12] P.-Y. Liu, H.-W. Lee, T.-Y. Li, S.L. Huang and S.-W. Hsu, “An Experimental Platform Based on MCE for Interactive TV," in Proc. of 6th European Interactive TV Conference , Salzburg, Austria, 2008.
    [13] J. Masthoff, “Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers,” in Proc. of User Modeling and User-Adapted Interaction, 14(1):37-85, 2004.
    [14] Y. Nakatoh, H. Kuwano, T. Kanamori and M. Hoshimi, ”Speech recognition interface system for digital TV control,” in Proc. of Acoustical Science and Technology, Vol. 28, pp. 165-171, 2007.
    [15] D. O’Sullivan, B. Smyth, D.C. Wilson, K. McDonald and A. Smeaton, “Improving the Quality of the Personalized Electronic Program Guide,” in Proc. of User Modeling and User-Adapted Interaction, 14(1): 5-36, 2004.
    [16] M. Pantic and L.J.M. Rothkrantz, ”Toward an Affect-Sensitive Multimodal Human-Computer Interaction,” in Proc. of the IEEE, 91(9):1370-1390, 2003.
    [17] H. Si, Y. Kawahara, H. and T. Aoyama, ”A Stochastic Approach for Creating Context-Aware Services based on Context Histories in Smart Home,” in Proc. of the 1st International Workshop on Exploiting Context Histories in Smart Environment, 2005.
    [18] M.V. Setten and M. Veenstra, ”Prediction Strategies in a TV Recommender System - Method and Experiments,” in Proc. of IADIS WWW/Internet 2003 Conference, 2003.
    [19] Z. Yu, X. Zhou, Y. Hao and J. Gu, “TV Program Recommendation for Multiple Viewers Based on user Profile Merging,” in Proc. of User Modeling and User-Adapted Interaction, 16(1):63-82, 2006.
    [20] J. Zimmerman and K. Kurapati, “Exposing Profiles to Build Trust in a Recommender,” in Proc. of Conference on Human Factors in Computing Systems, pp. 608-609, 2002.
    [21] 劉炳億, 劉家揚, 游鳳怡, 李宏偉, 黃淑麗, 李蔡彥, “以心理學實驗探討互動電視新功能之設計”, in Proc. of 2008 Symposium on Digital Life and Internet Technologies , Tainan.
    [22] Coding4Fun:Managed Library for Nintendo`s Wiimote,
    http://blogs.msdn.com/coding4fun/archive/2007/03/14/1879033.aspx.
    [23] CodeProject:AI – Neural network for beginners (Part1),
    http://www.codeproject.com/KB/recipes/NeuralNetwork_1.aspx.
    [24] CodeProject:Neural network on c#,
    http:// www.codeproject.com/KB/recipes/aforge_neuro.aspx.
    [25] TiVo, http://www.tgc-taiwan.com.tw/.
    [26] Wiimote, http://en.wikipedia.org/wiki/Wii_Remote.
    [27] 中華電信MOD, http://mod.cht.com.tw/MOD/Web/index.php.
    [28] 微軟MCE,
    http://www.microsoft.com/windows/products/windowsvista/features/details/mediacenter.mspx.
    Description: 碩士
    國立政治大學
    資訊科學學系
    95753027
    96
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095753027
    Data Type: thesis
    Appears in Collections:[Department of Computer Science ] Theses

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