• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.65-71
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• 2005

With the rapid improvement of the internet and information technology, digital contents containing knowledge and information resource is circulated through the internet. A circulation system based on a standardized identifier is required to share this kind of information, generated from seminars and workshops conducted in the area of science and technology and saved in the form of digital video contents. The main objective of this study is on constructing an information circulation system based on the KOI identifier to effectively share the digital video contents produced from seminars and workshops related to the area of science and technology. Furthermore, the overview and status of a standardized identifier, and the functional aspects of the system such as the methods to apply the KOI identification system on the subject and its slides of digital video contents, a digital video contents management system, a centralized identifier management system, and the methods applied for the search of digital video metadata have been suggested to support construction of the information circulation system.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.329-346
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• 2022

Recently, as the market for short form videos (Instagram, TikTok, YouTube) on social media has gradually increased, research using them is actively being conducted in the artificial intelligence field. A representative research field is Video to Shop, which detects fashion products in videos and searches for product images. In such a video-based artificial intelligence model, product features are extracted using convolution operations. However, due to the limitation of computational resources, extracting features using all the frames in the video is practically impossible. For this reason, existing studies have improved the model's performance by sampling only a part of the entire frame or developing a sampling method using the subject's characteristics. In the existing Video to Shop study, when sampling frames, some frames are randomly sampled or sampled at even intervals. However, this sampling method degrades the performance of the fashion product search model while sampling noise frames where the product does not exist. Therefore, this paper proposes a sampling method MF (Missing Fashion items on frame) sampler that removes noise frames and improves the performance of the search model. MF sampler has improved the problem of resource limitations by developing a keyframe mechanism. In addition, the performance of the search model is improved through noise frame removal using the noise detection model. As a result of the experiment, it was confirmed that the proposed method improves the model's performance and helps the model training to be effective.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.237-240
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• 2004

This paper describes a character retrieval system for TV programs and a set of novel algorithms for detecting and recognizing faces for the system. Our character retrieval system consists of two main components: Face Register and Face Recognizer. The Face Register detects faces in video frames and then guides users to register the detected faces of interest into the database. The Face Recognizer displays the appearance interval of each character on the timeline interface and the list of scenes with the names of characters that appear on each scene. These two components also provide a function to modify incorrect results. which is helpful to provide accurate character retrieval services. In the proposed face detection and recognition algorithms. we reduce the computation time without sacrificing the recognition accuracy by using the DCT/LDA method for face feature extraction. We also develop the character retrieval system in the form of plug-in. By plugging in our system to a cataloguing system. the metadata about the characters in a video can be automatically generated. Through this system, we can easily realize sophisticated on-demand video services which provide the search of scenes of a specific TV star.

• The Journal of Korean Association of Computer Education
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• v.5 no.1
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• pp.57-66
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• 2002

Real time multimedia data services have been made possible by the rapid development of the computer and internet technology. Based on the technology, Many multimedia system developer try to use VOD(Video on Demand) and GVA technologies for distance education. However the system has mainly been developed to provide the video screen of good quality in real time and to compose contents efficiently. Not many researches and developments have been made for providing the users that is taking distance education with various types of service using VOD and GVA. Therefore In this paper we have designed and implemented an active on-demand multimedia service system to improve user-side service quality in distance education using VOD and GVA service. The on-demand multimedia service system can prominently help users to save the time and effort to search and select the studying data by this paper enables off-line search functions through E-mail and periodical current awareness service supported by PUSH technology, user oriented information booking supported by SDI service and feedback service.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.57-60
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• 2000

Even if the video data is utilized for a lot of field, its very difficult to reuse and search easily because of its atypical(unfixed form) and complicated structure. In this study, we presented the video retrieval system which is based on the synchronized closed caption and video, SMIL and SAMI languages which are described to structured and systematic form like multimedia data These have next structure; At first, a key word is inputted by user, then time stamp would be sampling from the string which has a key word in the caption file. To the result, the screen shows an appropriate video frame.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.45-48
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• 2008

This paper presents a brief overview of scalable video coding (SVC) with a focus on spatial scalability and its application to Advanced Terrestrial-DMB (AT-DMB). By adopting SVC with two spatial-layers and hierarchical modulation, AT-DMB provides standard definition (SD)-level video while maintaining compatability with the existing CIF-level video. In this paper, we suggest a layer-configuration and coding parameters of SVC which are well suit for an AT-DMB system. In order to reduce extremely large encoding time resulted by an exhaustive search of a macroblock coding mode in spatial scalability, we propose a fast mode decision method which excludes redundant modes in each layer. It utilizes the mode distribution of each layer and their correlations. Experimental results show that a simplified encoding model with the method reduces the computational complexity significantly with negligible coding loss.

• Proceedings of the IEEK Conference
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• 2004.06b
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• pp.561-564
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• 2004

The motion estimation which requires huge computation consumes large power in a video encoder. Although a number of fast-search algorithms are proposed to reduce the power consumption, the smaller the computation, the worse the performance they have. In this paper, we propose an architecture that a low energy management scheme can be applied with several fast-search algorithm. In addition. we show that ECVH, a software scheduling scheme which dynamically changes the search algorithm, the operating frequency, and the supply voltage using the remaining slack time within given power-budget, can be applied to the architecture, and show that the power consumption can be reduced.

• Journal of Broadcast Engineering
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• v.8 no.3
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• pp.288-296
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• 2003

ATSC (Advanced Television System Committee) has specified 18 video formats for DTV (Digital Television), e.g., scan format, size format, and frame rate format conversion. Effective MPEG-2 video transcoders should support any conversion between the above-mentioned formats. Scan format conversion Is hard to Implement because it may often induce frame rate and size format conversion together. Especially. because of picture type conversion caused by scan format conversion, the computational burden of motion estimation (ME) in transcoding becomes serious. This paper proposes a fast ME algorithm for MPEG-2 video transcoding supporting scan format conversion. Firstly, we extract and compose a set of candidate motion vectors (MVs) from the input bit-stream to comply with the re-encoding format. Secondly, the best MV is chosen among several candidate MVs by using a weighted median selector. Simulation results show that the proposed ME algorithm provides outstanding PSNR performance close to full search ME, while reducing the transcoding complexity significantly.