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The quality of digital content has become increasingly significant in the digitalized broadcasting world. These days, consumers react even to subtle defects in media content, which in turn, influence consumer satisfaction about the entire content. The development of digital broadcasting technology has replaced tape-based content with file-based content. Nonetheless, in the process of generating file-based content, people are often confronted with different types of errors. Detecting such errors and fixing them requires a substantial amount of time and human labor, while being unable to fix them might lead to broadcast failure. Therefore in this paper, we introduce an automated restoration system that reduces intensive human labor in fixing the errors in the content generation process. Our automated video restoration system can be applied to different types of classical errors. We developed several algorithms to restore each error in the digital content derived from the KBS video archive. Implementing our method using a tool already familiar to content producers has also been one of our considerations. We are developing the restoration system as a plug-in to a well-known NLE (Non-linear editing system).

N-Screen service has experienced rapid business expansion recently, since consumers' watching patterns have been diversified; also business stakeholders including broadcasting companies, internet service providers, and device manufacturers have joined this field. In order to operate N-Screen service in a stable manner, development of advertisement system where it generates continuous advertisement profit is needed. Especially for a streaming service that delivers live TV programs, the new advertising system has to deliver ads in conjunction with the live streaming system that is in use. In this paper, video advertising system that is congenial to N-Screen is proposed. Both real time video/ad converting scheme and direct video ads delivery function were developed and tested. In addition, ad contents management and statistics management functions have been developed for advertisement managers. This system was implemented in a commercial N-Screen service and it is currently being used for delivering video advertisements. Keyword : advertising system, N-Screen service, multi-screen advertising, live streaming 정규논문 (Regular Paper) 방송공학회논문지 제19권 제6호, 2014년 11월 (JBE Vol. 19, No. 6, November 2014) http://dx.doi.org/10.5909/JBE.2014.19.6.957 ISSN 2287-9137 (Online) ISSN 1226-7953 (Print) 958 방송공학회논문지 제19권 제6호, 2014년 11월 (JBE Vol. 19, No. 6, November 2014) 그림 1. N-스크린 서비스 예제-KBS 통합플레이어K (모바일 및 PC용) Fig. 1. KBS N-Screen service 'Player-K' I. 서 론 기존의 일 방향 방송 서비스는 통신 네트워크의 성능이 고도화 되고 소비자의 콘텐츠 소비 패턴, 니즈가 다양화 되 면서 언제 어디서나 원하는 단말기를 통해서 원하는 콘텐 츠를 즐길 수 있는 N-스크린 서비스로 진화하고 있다. 또한 방송사업자 뿐만 아니라 미디어/콘텐츠 사업자, 통신 사업자, 인터넷 포털 사업자, 단말기 제조사 등도 N-스크린 서비스 사업에 참여하면서 사업 영역이 확대되고 N-스크린 서비스는 활기를 띠게 되었다 . 그러나 경쟁적인 환경 에서 N-스크린 서비스가 완전히 정착되고 지속적으로 서비 스되기 위해서는 안정적인 수익원이 필요하며, 그 중 하나 로 광고에 대한 관심이 클 수밖에 없다. N-스크린 서비스에서 활용할 수 있는 광고는 여러 형태 가 있지만, 인터넷에서 많이 활용되어 왔던 배너 광고는 영 상 콘텐츠 시청이 주요 활동이 되는 N-스크린 화면에서 활 용도가 떨어지는 반면, 동영상 광고의 경우 기존 TV 광고 와 같은 형태로 영상 콘텐츠 사이에 광고를 배치하는 방법 으로 시청자의 주목도를 높일 수 있어 유용한 광고 방식이 된다. 동영상 광고를 제공하기 위해 기존 인터넷상에서는 PC(personal computer)의 브라우저에서 동작하는 다양한 기능들을 활용해 왔으나, PC보다 제약이 많은 모바일 단말 기 까지 서비스 대상이 확장되면서 다양한 단말기에도 함 께 광고를 제공할 수 있는 기술 개발이 요구되고 있다. 특히 VOD(Video on demand)를 제공하는 시스템과 달리 실시간 방송을 제공하는 N-스크린 서비스의 경우 동영상 광고를 제공하기 위한 기술이 별도로 필요하다. 본 연구에서는 실시간 방송을 위한 N-스크린 서비스에서 동영상 광고를 제공하기 위해 필요한 기술을 제안하고 이 를 구현하였다. 이에 대한 설명으로 다음 장에서는 N-스크 린 실시간 방송을 제공하기 위해 방송사에서 이용하는 기 본적인 시스템 구조와 이를 지원하는 기술에 대해 알아보 고, 3장에서는 이를 확장하여 동영상 광고를 제공하기 위해 본 논문에서 제안하는 시스템에 대해 설명한다. 4장에서는 실제로 구현된 시스템이 적용된 내용을 보여주고, 5장에서 결론 내용을 서술한다. II. N-스크린 실시간 방송 제공 시스템

As the resolution of TV significantly increased, content consumers have become increasingly sensitive to the subtlest defect in TV contents. This rising standard in quality demanded by consumers has posed a new challenge in today’s context where the tape-based process has transitioned to the file-based process: the transition necessitated digitalizing old archives, a process which inevitably produces errors such as disordered pixel blocks, scattered white noise, or totally missing pixels. Unsurprisingly, detecting and fixing such errors require a substantial amount of time and human labor to meet the standard demanded by today’s consumers. In this paper, we introduce a novel, automated error restoration algorithm which can be applied to different types of classic errors by utilizing adjacent images while preserving the undamaged parts of an error image as much as possible. We tested our method to error images detected from our quality check system in KBS(Korean Broadcasting System) video archive. We are also implementing the algorithm as a plugin of well-known NLE(Non-linear editing system), which is a familiar tool for quality control agent.

This paper presents a system architecture and information retrieval strategy for multimedia content which exploits descriptive metadata as well as domain ontology. We propose a query processing model including a semantic ranking scheme which can retrieve multimedia objects semantically relevant to the user query and provide users with a search result categorized by concepts and ordered by their semantic relevance to the query. By experiments on a prototype system using a repository of broadcast TV programs, we show effectiveness of the ontology-based multimedia search approach proposed in the paper.

This article proposes a novel video abstraction framework for online review services of story-oriented videos such as dramas. Among the many genres of TV programs, a drama is one of the most popularly watched on the Web. The abstracts generated by the proposed framework not only give a summary of a video but also effectively help viewers understand the overall story. In addition, our method is duration-flexible. We get clues about human understanding of a story from scenario writing rules and editorial techniques that are popularly used in the process of video production to explicitly express a narrative, and propose a new video abstraction model, called a Narrative Abstraction Model . The model effectively captures the narrative structure embedded in a story-oriented video and articulates the progress of the story in a weighted directed graph, called a Narrative Structure Graph (NSG) . The model provides a basis for a flexible framework for abstract generation using the NSG as the intermediary representation of a video. Different abstracts can be appropriately generated based upon different user requirements. To show the effectiveness of the proposed model and method, we developed a video abstraction system realizing the framework, and successfully applied it to large volumes of TV dramas. The evaluation results show that the proposed framework is a feasible solution for online review services.