• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.71-80
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• 2003

In this Paper, we Propose web-based Media GIS architecture using 3D geographical database and GPS-related data resulted from 45-Van. We introduce a novel interoperable geographical data service concept; so-called, Virtual World Mapping (VWM) that can map 3D graphic world with real-world video. Our proposed method can easily retrieve geographical information and attributes to reconstruct 3D virtual space according to certain frame in video sequences. Our proposed system architecture also has an advantage that can provide geographical information service with video stream without any image processing procedures. In addition to, describing the details of our components, we present a Media GIS web service system by using GeoVideoServer, which performs VWM technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2444-2463
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• 2020

Significant detection of video can more rationally allocate computing resources and reduce the amount of computation to improve accuracy. Deep learning can extract the edge features of the image, providing technical support for video saliency. This paper proposes a new detection method. We combine the Convolutional Neural Network (CNN) and the Deep Bidirectional LSTM Network (DB-LSTM) to learn the spatio-temporal features by exploring the object motion information and object motion information to generate video. A continuous frame of significant images. We also analyzed the sample database and found that human attention and significant conversion are time-dependent, so we also considered the significance detection of video cross-frame. Finally, experiments show that our method is superior to other advanced methods.

• Journal of KIISE:Software and Applications
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• v.26 no.9
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• pp.1052-1060
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• 1999

이제까지 비디오 데이타베이스를 모델링하기 위한 많은 연구들이 수행되었지만 그 모든 모델들에서 다루는 비디오 데이타는 사용자의 개입이 없을 때 항상 미리 정의된 순서로 보여진다는 점에서 정적 데이타 모델로 간주될 수 있다. 주문형 뉴스 서비스, 주문형 비디오 서비스, 디지털 도서관, 인터넷 쇼핑 등과 같이 최신 비디오 정보 서비스를 제공하는 비디오 데이타베이스 응용들에서는 빈번한 비디오 편집이 요구되는데 실시간 처리가 바람직하다. 이를 위해서 기존의 비디오 데이타 내용이 변경되거나 새로운 비디오 데이타가 생성되어야 하지만 이제까지의 비디오 데이타 모델에서는 이러한 비디오 편집 작업이 일일이 수작업으로 수행되어야만 했다. 본 논문에서는 비디오 편집에 드는 노력을 줄이기 위해서 객체지향 데이타 모델에 기반하여 DVID(Dynamic Video Object Data Model)라는 동적 비디오 객체 데이타 모델을 제안한다. DVID는 기존의 정적 비디오 객체뿐만 아니라 사용자의 개입없이도 비디오의 내용을 비디오 데이타베이스로부터 동적으로 결정하여 보여주는 동적 비디오 객체도 함께 제공한다.Abstract A lot of research has been done on modeling video databases, but all of them can be considered as the static video data model from the viewpoint that all video data on those models are always presented according to the predefined sequences if there is no user interaction. For some video database applications which provides with up-to-date video information services such as news-on-demand, video-on-demand, digital library, internet shopping, etc., video editing is requested frequently, preferably in real time. To do this, the contents of the existing video data should be changed or new video data should be created, but on the traditional video data models such video editing works should be done manually. In order to save trouble in video editing work, this paper proposes the dynamic video object data model named DVID based on object oriented data model. DVID allows not only the static video object but also the dynamic video object whose contents are dynamically determined from video databases in real time even without user interaction.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.252-264
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• 1999

The key characteristic of video data is its spatial/temporal relationships. In this paper, we propose an content based video retrieval system based on hierarchical data structure for specifying the temporal semantics of video data. In this system, video data's hierarchical structure temporal relationship, inter video object temporal relationship, and moving video object temporal relationship can be represented. We also implemented these video data's temporal relationship into an object-relational database management system using inheritance, encapsulation function overloading, etc. So more extended and richer temporal functions can be used to support a broad range of temporal queries.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.107-116
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• 1998

Video data are retrieved and stored in various compressed forms according to their characteristics. In this paper, we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream. Using this model, we design and implement CVIMS (the MPEG-2 Compressed Video Information Management System) to store and retrieve video documents. CVIMS extracts I-frames from MPEG-2 TS files, selects key-frames from the I-frames, and stores in database the index information such as thumbnails, captions, and picture descriptors of the key-frames. And, CVIMS retrieves MPEG-2 video data using the thumbnails of key-frames and various labels of queries. And also, the system is accessible by a web interface.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.2-9
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• 2000

This paper presents a statistical motion activity description method and video retrievals by using the intensity and directions of the extracted motion vectors from video sequence. Since the proposed method can represent temporal and spatial cognitive characteristics of an entire video, several images between key frames, and images in a certain interval, it can be effectively applied to digital video services such as video retrieval, surveilance, multimedia database, and broadcasting filterings. In the paper, the effectiveness of the proposed algorithm is shown with a lot of shots of MPEG-7 video dataset.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1431-1440
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• 1998

Video data are retrieved and stored in various compressed forms according to their characteristics, In this paper, we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream, Using this model, we design and implement CVIMS (the MPEG-2 Compressed Video Information Management System) to store and retrieve video documents, CVIMS extracts I-frames from MPEG-2 files, selects key-frames from the I -frames, and stores in database the index information such as thumbnails, captions, and picture descriptors of the key-frames, And also, CVIMS retrieves MPEG- 2 video data using the thumbnails of key-frames and v31ious labels of queries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.439-442
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• 2004

Traditional database systems have been used models supported for the operations and relationships based on simple interval. video data models are required in order to provide supporting temporal paradigm, various object operations and temporal operations, efficient retrieval and browsing in video model. As video model is based on object-oriented paradigm, 1 present entire model structure for video data through the design of metadata which is used of logical schema of video, attribute and operation of object, and inheritance and annotation. by using temporal paradigm through the definition of time point and time interval in object-oriented based model, we tan use video information more efficiently by me variation.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.494-506
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• 2003

Recently, explosive popularity of multimedia information has triggered the need for retrieving multimedia contents efficiently from the database including audio, video and images. In this paper, we propose an XML-based retrieval scheme and a data model that complement the weak aspects of annotation and conent based retrieval methods. The Property and hierarchy structure of image and video data are represented and manipulated based on the Multimedia Description Schema (MDS) that conforms to the MPEG-7 standard. For audio contents, pitch contours extracted from their acoustic features are converted into UDR string. Especially, to improve the retrieval performance, user's access pattern and frequency are utilized in the construction of an index. We have implemented a prototype system and evaluated its performance through various experiments.