• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.32-37
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• 2008

To ensure access to rapidly growing video collection, video indexing is becoming more and more important. In this paper, video ontology system for retrieving a video data based on a scene unit is proposed. The proposed system creates a semantic scene as a basic unit of video retrieval, and limits a domain of retrieval through a subject of that scene. The content of semantic scene is defined using the relationship between object and event included in the key frame of shots. The semantic gap between the low level feature and the high level feature is solved through the scene ontology to ensure the semantic-based retrieval.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.105-112
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• 2002

In order to process video data effectively, we need to save its content on database and a content-based retrieval method which processes various queries of all users is required. In this paper, we present VRS(Video Retrieval System) which provides similarity query, SQBE(Scene Query By Example) query, and content-based retrieval by combining the feature-based retrieval and the annotation-based retrieval. The SQBE query makes it possible for a user to retrieve scones more exactly by inserting and deleting objects based on a retrieved scene. We proposed query language and query processing algorithm for SQBE query, and carried out performance evaluation on similarity retrieval. The proposed system is implemented with Visual C++ and Oracle.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1057-1060
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• 1999

For efficient storage and retrieval of large video data sets, automatic video scene change detection is a necessary tool. Video scene changes fall into two categories, namely fast and gradual scene changes. The gradual scene change effects include, dissolves, wipes, fades, etc. Although currently existing algorithms are able to detect fast scene changes quite accurately, the detection of gradual scene changes continue to remain a difficult problem. In this paper, among various gradual scene changes, we focus on dissolves. The algorithm uses a subset of the entire video, namely the sequence of DC images, for improvement of detection velocity

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1129-1133
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• 2006

In this thesis, we propose a semantics-based video retrieval system which supports semantics-retrieval for various users of massive video data. Proposed system automatically processes the extraction of contents information which video data has and retrieval process using agent which integrate annotation-based retrieval and feature-based retrieval. From experiment, the designed and implemented system shows increase of recall rate and precision rate for video data scene retrieval in performance assessment.

• Journal of Internet Computing and Services
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• v.3 no.2
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• pp.69-77
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• 2002

Recently, Digital video is one of the important information media delivered on the Internet and playing an increasingly important role in multimedia. This paper proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web, For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combines the RGB color histogram with the $x^2$(Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing, This system involves the video editing and retrieval function of a VCR's, Three elements that are the date, the field and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.761-766
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• 2005

This paper proposes a video model for the implementation of the cultural video database system. We have utilized an efficient scene change detection method that segments cultural video into semantic units for efficient indexing and retrieval of video. Since video has a large volume and needs to be played for a longer time, it implies difficulty of viewing the entire video. To solve this Problem. the cultural video abstraction was made to save the time and widen the choices of video the video abstract is the summarization of scenes, which includes important events produced by setting up the abstraction rule.

• International Journal of Contents
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• v.4 no.2
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• pp.24-28
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• 2008

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.211-214
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• 2002

Automatic video partitioning is the first step for content-based indexing and retrieval of video data. In this paper, an efficient algorithm for scene change detection is proposed, where cumulative histogram and edge information are utilized. Experimental results have shown the effectiveness of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.147-154
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• 2006

Effective and efficient representation of color features of multiple video frames is an important vet challenging task for visual information management systems. This paper Proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web. For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combine the RGB color histogram with the X2 (Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing. This system involves the video editing and retrieval function of a VCR's. Three elements that are the date, the need and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.629-637
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• 2000

The content-based information retrieval for a multimedia database uses feature information extracted from the compressed videos. This paper presents an effective method to detect scene changes from compressed videos. Scene changes are detected with DC values of DCT coefficients in MPEG-1 encoded video sequences. Instead of decoding full frames. partial macroblocks of each frame, horizontal and vertical macroblocks, are decoded to detect scene changes. This method detects abrupt scene changes by decoding minimal number of blocks and saves a lot of computation time. The performance of the proposed algorithm is analyzed based on the precision and the recall. The experimental results show the effectiveness in computation time and detection rate to detect scene changes of various MPEG-1 video streams.