• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.621-628
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• 2000

A retrieval performance of VOD sever is estimated by how quickly it services popular videos to users and how many users it is able to service. Each video data is placed on heterogeneous disks and placement techniques are various, retrieval performance is under the control of these elements, so that a retrieval performance is affected by placement policy. In this paper, we place video data considering their characteristics, especially, we place videos distributively according to their popularity. To verify our policy, we make various environment of experiment, estimate a placement policy using popularity of videos and a contrary policy, and compare them.

• Journal of Information Science Theory and Practice
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• v.4 no.4
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• pp.4-15
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• 2016

Information needs of users have been examined both generally and as they pertain to particular types and formats of information. Barriers to information have also been investigated, including those which are situational and also across certain domains and socioeconomic contexts. Unified studies concerning both information needs and barriers are needed. Both are likely always present in any given interactive search situation; further, users' attempts to satisfy their own individualized information needs will likely encounter barriers of some sort. The present study employed a survey method to collect users' perceptions of video information needs and barriers as part of recent video search situations. Findings from this analysis establish a unified framework, based on the themes emerging directly from the responses of users, and present the suitability and benefit for informing future designs and evaluations of user-centered interactive retrieval tools.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.913-924
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• 2000

This paper proposes an efficient descriptor for objects motion trajectory and a video retrieval algorithm based on objects motion trajectory. The algorithm describes parameters with coefficients of 2-order polynomial for objects motion trajectory after segmentation of the object from the scene. The algorithm also identifies types, intervals, and magnitude of global motion caused by camera motion and indexes them with 6-affine parameters. This paper implements content-based video retrieval using similarity-match between indexed parameters and queried ones for objects motion trajectory. The proposed algorithm will support not only faster retrieval for general videos but efficient operation for unmanned video surveillance system.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2287-2297
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• 2000

Video documents which have audio-visual and other semantics information have complex relationship among media. While user requests for topic retrieval or specific region retrieval increase, it is difficult to meet these requests with the existing design methodology, In order to support the systematic management and the various retrieval capabilities of video document, we must formulate structural and systematic model on metadata using semantics and structural informations which are abstracted automaticallv or manuallv. This paper suggests generic metadata model with which we analyze the characteristics of video document, supports various query types and serves as a generic framework for video applications, we propose the generic integrated management model(GIMM)for generic metadata,, design video documents management system(VDMS) and implement it using GIMM.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.705-710
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• 2003

Recent years, as a rapid development of multimedia technology, video database system to retrieve video data efficiently seems to core technology in the oriented society. This thesis describes an efficient automatic frame detection and location method for content based retrieval of video. Frame extraction part is consist of incoming / outgoing car frame extraction and car number frame extraction stage. We gain star/end time of car video also car number frames. Frames are selected at fixed time interval from video and key frames are selected by color scale histogram and edge operation method. Car frame recognized can be searched by content based retrieval method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.30-36
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• 2008

The multimedia that is characterized by multi-media, multi-features, multi-representations, huge volume, and varieties, is rapidly spreading out due to the increasing of application domains. Thus, it is urgently needed to develop a multimedia information system that can retrieve the needed information rapidly and accurately from the huge amount of multimedia data. For the content-based retrieval of moving picture, picture information is generally used. It is generally used when video is segmented. Through that, it can be a structural video browsing. The tasking that divides video to shot is called video segmentation, and detecting the cut for video segmentation is called cut detection. The goal of this paper is to divide moving picture using HMMD(Hue-Mar-Min-Diff) color model and edge histogram descriptor among the MPEG-7 visual descriptors. HMMD color model is more familiar to human's perception than the other color spaces. Finally, the proposed retrieval system is implemented as hardware.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.12
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• pp.756-771
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• 2003

Digital Video Library System which manages a large amount of multimedia information requires efficient and effective retrieval methods. In this paper, we propose and implement a new video search and retrieval algorithm that compares the query video shot with the video shots in the archives in terms of foreground object, background image, audio, and its context. The foreground object is the region of the video image that has been changed in the successive frames of the shot, the background image is the remaining region of the video image, and the context is the relationship between the low-level features of the adjacent shots. Comparing these features is a result of reflecting the process of filming a moving picture, and it helps the user to submit a query focused on the desired features of the target video clips easily by adjusting their weights in the comparing process. Although the proposed search and retrieval algorithm could not totally reflect the high level semantics of the submitted query video, it tries to reflect the users' requirements as much as possible by considering the context of video clips and by adjusting its weight in the comparing process.

• Journal of the Korea Society of Computer and Information
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• v.3 no.4
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• pp.10-18
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• 1998

Video information is an important component of multimedia system such as Digital Library. World-Wide Web(WWW) and Video-On-Demand(VOD) service system. It can support various types of information because of including audio-visual, spatial-temporal and semantics information. In addition, it requires the ability of retrieving the specific scene of video instead of entire retrieval of video document. Therefore, so as to support a variety of retrieval, this paper models metadata using video document structure information that consists of hierarchical structure, and designs database schema that can manipulate video document.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8649-8653
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• 2015

A number of video indexing and retrieval algorithms have been proposed to manage large video databases efficiently. The video similarity measure is one of most important technical factor for video content management system. In this paper, we propose the luminance characteristics model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient similarity measure using the luminance projection. To index the video sequences effectively and to reduce the computational complexity, we calculate video similarity using the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed luminance projection model yields the remarkable improved accuracy and performance than the conventional algorithm such as the histogram comparison method, with the low computational complexity.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.1017-1028
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• 2007

In this paper we propose an effective method to represent, store, and retrieve video streams efficiently from a video database. We extract features from each video frame, normalize the feature values, and represent them as values in the range [0,1]. In this way a video frame with f features can be represented by a point in the f-dimensional space $[0,1]^f$, and thus the video stream is represented by a trail of points in the multidimensional space. The video stream is partitioned into video segments based on camera shots, each of which is represented by a trend vector which encapsulates the moving trend of points in a segment. The video stream query is processed depending on the comparison of those trend vectors. We examine our method using a collection of video streams that are composed of sports, news, documentary, and educational videos. Experimental results show that our trend vector representation reduces a reconstruction error remarkably (average 37%) and the retrieval using a trend vector achieves the high precision (average 2.1 times) while maintaining the similar response time and recall rate as existing methods.