• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.662-676
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• 2008

This paper presents a video copy detection algorithm that blocks online transfer of illegally copied DTV broadcast programs. Particularly, the proposed algorithm establishes a set of keyframes by detecting abrupt changes of luminance, and then exploits the spatio-temporal features of keyframes. Comparing with the preregistered features stored in the database of DTV broadcast programs, the proposed scheme performs a function of video filtering in order to distinguish whether an uploaded video is illegally copied or not. Note that we analyze only a set of keyframes instead of an entire video frame. Thus, it is highly efficient to identify illegal copied video when we deal with a vast size of broadcast programs. Also, we confirm that the proposed technique is robust to a variety of video edit-effects that are often applied by online video redistribution, such as apsect-ratio change, logo insertion, caption insertion, visual quality degradation, and resolution change (downscaling). In addition, we perform a benchmark test in which the proposed scheme outperforms previous techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1716-1722
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• 2021

Recently, the capacity of video content delivery services has been increasing significantly. Therefore, the importance of user recommendation is increasing. In addition, these contents contain a variety of characteristics, making it difficult to express the characteristics of the content properly only with a few keywords(Elements used in the search, such as titles, tags, topics, words, etc.) specified by the user. Consequently, existing recommendation systems that use user-defined keywords have limitations that do not properly reflect the characteristics of objects. In this paper, we compare the efficiency of between a method using voice data-based subtitles and an image comparison method using keyframes of images in recommendation module of educational video service systems. Furthermore, we propose the types and environments of video content in which each analysis technique can be efficiently utilized through experimental results.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2294-2301
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• 1998

The aim of this paper is to extract features from each news scenes for example, symbol icon which can be distinct each broadcasting corp, icon and caption which are has feature and important information for the scene in respectively, In this paper, we propose extraction methods of caption that has important prohlem of news videos and it can be classified in three steps, First of al!, we converted that input images from video frame to YIQ color vector in first stage. And then, we divide input image into regions in clear hy using equalized color histogram of input image, In last, we extracts caption using edge histogram based on vertical and horizontal line, We also propose the method which can extract news icon in selected key frames by the difference of inter-histogram and can divide each scene by the extracted icon. In this paper, we used comparison method of edge histogram instead of complex methcxls based on color histogram or wavelet or moving objects, so we shorten computation through using simpler algorithm. and we shown good result of feature's extraction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.563-565
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• 2021

The most important feature of the recently increasing content providing service is that the amount of content increase over time is very large. Accordingly, the importance of user curation is increasing, and various techniques are used to implement it. In this paper, among the techniques for video recommendation, the analysis technique using voice data and subtitles and the video comparison technique based on keyframe extraction are compared with the results of implementing and applying the video content of real big data. In addition, through the comparison result, a video content environment to which each analysis technique can be applied is proposed.

• Journal of Broadcast Engineering
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• v.8 no.1
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• pp.63-71
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• 2003

In sport programs, real-time virtual imaging system come into notice for new technology which can compose information like team logos, scores. distances directly on playing ground, so it can compensate for the defects of general character generator. In order to synchronize graphics to camera movements, generally two method is used. One is for using sensors attached to camera moving axis and the other is for analyzing camera video itself. KBS technical research institute developed real-time sensor-based virtual imaging system 'VIVA', which uses four sensors on pan, tilt, zoom, focus axis and controls virtual graphic camera in three dimensional coordinates in real-time. In this paper, we introduce our system 'VIVA' and it's technology. For accurate camera tracking we calculated view-point movement occurred by zooming based on optical principal point variation data and we considered field of view variation not only by zoom but also by focus. We developed our system based on three dimensional graphic environment. so many useful three dimensional graphic techniques such as keyframe animation can be used. VIVA was successfully used both in Busan Asian Games and 2002 presidential election. We confirmed that it can be used not only in the field but also in the studio programs in which camera is used within more close range.