• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2442-2451
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• 2000

Recently, there have been some trials to use a TV system as an Internet terminal for easier and more convenient use of Internet. Because a TV Web browser system has a TV display with a set-top box as an execution environment, it has some limits and there are specific requirements. The efficient implementation of the Web browser for TV needs the proxy server that includes HTML conversions for TV environments as well as general cash functions. In order to implement a Web environment on general TV and set-tops, we introduce a distributed structure using a proxy server and propose TV - HTML conversions as an important feature of the proxy server.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.683-692
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• 2003

The rapid increase of the number of channels makes it hard to find wanted programs from TV. In recent years, the number of channels come up to hundreds with the digital TV arrival. So, it will drive us to the new way of watching TV. In this paper, we introduce a recommendation system for TV programs to overcome this difficulty. We model user profiles and design each module of the system, considering TV environment. Our system gathers basic information from people manually and then updates user profiles automatically by tracking viewing and usage history. As a result, our system recommends daily TV programs based on the changing interest of users. In this paper, we address the problems and solutions by describing our system and the experiment.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.557-565
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• 2012

Objective: This paper focuses on the new trend of applying NUI(natural user interface) such as gesture interaction into television and investigates on the design improvement needed in application. The intention is to find better design direction of NUI on television context, which will contribute to making new features and behavioral changes occurring in next-generation television more practically usable and meaningful use experience elements. Background: Traditional television is rapidly evolving into next-generation television thanks to the influence of "smartness" from mobile domain. A number of new features and behavioral changes occurred from such evolution are on their way to be characterized as the new experience elements of next-generation television. Method: A series of expert review by television UX professionals based on AHP (Analytic Hierarchy Process) was conducted to check on the "relative appropriateness" of applying gesture interaction to a number of selected television user experience scenarios. Conclusion: It is critical not to indiscriminately apply new interaction techniques like gesture into television. It may be effective in demonstrating new technology but generally results in poor user experience. It is imperative to conduct consistent validation of its practical appropriateness in real context. Application: The research will be helpful in applying gesture interaction in next-generation television to bring optimal user experience in.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.50-53
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• 2013

스마트 폰의 등장으로 인해 사용자들은 모바일 기기를 통해 언제 어디서나 인터넷 서비스를 이용할 수 있게 되었고 더불어 다양한 앱을 통해 기존에 PC에서 제공되던 서비스들이 모바일 기기로 이동하게 되었다. 이러한 변화는 TV시장에도 영향을 미치게 되었고 TV에서도 인터넷 서비스뿐만 아니라 다양한 앱 서비스를 이용할 수 있는 스마트TV 시대를 열게 되었다. 스마트 TV시스템은 방송망과 인터넷 망을 통해 사용자에게 보다 다양한 멀티미디어 콘텐츠 서비스를 제공할 수 있게 되었으나 각 인터넷 콘텐츠 제공자가 앱 형태로 콘텐츠를 제공함으로써 다양한 콘텐츠 제공자로부터 사용자가 원하는 멀티미디어 콘텐츠를 검색하는 데에 한계가 있었다. 본 논문은 사용자 키워드 검색문 의미해석을 통해 서로 상이한 멀티미디어 콘텐츠 메타데이터 정보 구조를 가지고 있는 콘텐츠 제공자들이 효과적으로 검색결과를 제공할 수 있는 스마트TV통합검색시스템에 대하여 기술한다.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.925-937
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• 2003

The input of digital TV software is the Transport Stream, which utilizes the moving picture compression technique, MPEC-2 (Moving Picture Experts Groups-2). MPEG-2 TS consists of the complicated table hierarchy and internal relationships, as well as the various restrictions with regards to system standard of digital TV software in determining the field values of transport stream. However, the general MPEG-2 TS generation tool produces transport streams solely based on the MPEG-2 TS specification itself, and does not consider the interaction between modulo features or modules themselves, which construct digital TV software. In this paper, we propose a method to systematically generate MPEG-2 TS test data, namely‘Test Stream’, for digital TV software. We present the experiment result where the test stream derived from our developed tool according to the proposed method was applied to the actual digital TV software settop-box, and then analyze the result. Apart from other existing MPEG-2 TS generation tools, the advantage of our method is that not only is it capable of generating various levels of test streams including digital TV software module, integration, and system testing, but also detecting errors and analyzing their causes.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.347-358
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• 2014

A smart TV is able to show terrestrial broadcasting and also can be used as a computer -VOD, games, image communications, application utilities and so on. In order to carry out Smart TV business, it has to contains contents, platforms, network terminal unit. If ill-equipped with any of these aboves, it must cooperate with other licensee. Therefore, Smart TV business is necessary to cooperate with each business agent. In this paper, we will look into domestic/foreign country Smart TV market, policy, vitalization strategy, and suggest the application of big data analysis methodology for Smart TV vitalization method - 1) hardware infrastructure building based on cloud computing 2) Network upgradability acceptable traffic increase 3) Technical development cooperation between each licensee 4) Variable Smart TV contents supply 5) Cooperation with party interested individuals in using UX/UI for N-Screen, network traffic estimation may increase, customized supply smart contents for consumer in real time.

• Archives of design research
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• v.20 no.3 s.71
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• pp.257-268
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• 2007

The development of Human Computer Interface has been relied on the development of technology. Mice and keyboards are the most popular HCI devices for personal computing. However, device-based interfaces are quite different from human to human interaction and very artificial. To develop more intuitive interfaces which mimic human to human interface has been a major research topic among HCI researchers and engineers. Also, technology in the TV industry has rapidly developed and the market penetration rate for big size screen TVs has increased rapidly. The HDTV and digital TV broadcasting are being tested. These TV environment changes require changes of Human to TV interface. A gesture recognition-based interface with a computer vision system can replace the remote control-based interface because of its immediacy and intuitiveness. This research focuses on how people use their hands or arms for command gestures. A set of gestures are sampled to control TV set up by focus group interviews and surveys. The result of this paper can be used as a reference to design a computer vision based TV interface.

• Journal of the HCI Society of Korea
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• v.9 no.1
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• pp.23-28
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• 2014

In this study we focus on the effect of the interaction between humans and reactive television when emotion recognition through facial expression mechanism is used. Most of today's user interfaces in electronic products are passive and are not properly fitted into users' needs. In terms of the user centered device, we propose that the emotion based reactive television is the most effective in interaction compared to other passive input products. We have developed and researched next generation cognitive TV models in user centered. In this paper we present a result of the experiment that had been taken with Fraunhofer IIS $SHORE^{TM}$ demo software version to measure emotion recognition. This new approach was based on the real time cognitive TV models and through this approach we studied the relationship between humans and cognitive TV. This study follows following steps: 1) Cognitive TV systems can be on automatic ON/OFF mode responding to motions of people 2) Cognitive TV can directly select channels as face changes (ex, Neutral Mode and Happy Mode, Sad Mode, Angry Mode) 3) Cognitive TV can detect emotion recognition from facial expression of people within the fixed time and then if Happy mode is detected the programs of TV would be shifted into funny or interesting shows and if Angry mode is detected it would be changed to moving or touching shows. In addition, we focus on improving the emotion recognition through facial expression. Furthermore, the improvement of cognition TV based on personal characteristics is needed for the different personality of users in human to computer interaction. In this manner, the study on how people feel and how cognitive TV responds accordingly, plus the effects of media as cognitive mechanism will be thoroughly discussed.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.105-110
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• 2009

Conventional TV viewing environment had provided limited numbers of channels and contents so that accessibility of contents was made user's manual change of TV channels and by manual selection of TV program contents. However, with advent of IPTV and various contents and channels available to users’ terminals, excessive numbers of TV contents become available to users’ terminals, thus leading to totally different TV viewing environments. In this TV environment, users are required to make much effort to choose their preferred TV channels or program contents, which becomes much cumbersome to the users. Therefore, in this paper, we will propose TV contents schedule recommendation by making reasoning on users’ TV viewing patterns from TV viewing history data using sequential pattern mining so that so that it increases accessibility of users to many TV program contents which may be or may not be aware of the users.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.4
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• pp.73-79
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• 2013

Recently, smart TVs have widely spread in our daily lives. However, it is difficult for users to find proper TV contents among a lot of TV and application contents because of inconvenience of input devices compared with those of smart phones or smart pads, so there are some problems with very low utilization of the smart functionalities of smart TVs. We suggest a personalized contents recommender system on smart TVs to resolve these problems and help for users to search appropriate contents easily and quickly in this research. We design and implement an intelligent system for personalized contents recommendation on the smart TVs based on multi-dimensional analysis considering user profiles and preferences, watching patterns of TV programs, and TV contents use statistics of TV users.