• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.95-102
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• 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 Korea Multimedia Society
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• v.8 no.2
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• pp.269-278
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• 2005

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantics-based retrieval method can be available for various queries of users. In this paper, we propose a video retrieval system which support semantics retrieval of various users for massive video data by user's keywords and comparison area learning based on automatic agent. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user becomes a query image and searches the most similar key frame through color histogram comparison and comparison area learning method that proposed. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 93 percents.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.701-708
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• 2004

Existing contents-based video retrieval systems search by using a single method such as annotation-based or feature-based retrieval. Hence, it not only shows low search efficiency, but also requires many efforts to provide system administrator or annotator with a perfect automatic processing. Tn this paper, we propose an agent-based, and automatic and unified semantics-based video retrieval system, which support various semantics-retrieval of the massive video data by integrating the feature-based retrieval and the annotation-based retrieval. The indexing agent embodies the semantics about annotation of extracted key frames by analyzing a fundamental query of a user and by selecting a key-frame image that is ed by a query. Also, a key frame selected by user takes a query image of the feature-based retrieval and the indexing agent searches and displays the most similar key-frame images after comparing query images with key frames in the database by using the color-multiple-partition histogram techniques. Furthermore, it is shown that the performance of the proposed system can be significantly improved.

• Journal of KIISE:Databases
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• v.30 no.1
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• pp.14-26
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• 2003

Moving objects' trajectories play an important role in indexing video data on their content and semantics for content-based video retrieval. In this paper, we propose new similar sub-trajectory retrieval schemes based on k-warping algorithm for efficient retrieval on moving objects' trajectories in video data. The proposed schemes are fixed-replication similar sub-trajectory retrieval(FRSR) and variable-replication similar sub-trajectory retrieval(VRSR). The former can replicate motions with a fixed number for all motions being composed of the trajectory. The latter can replicate motions with a variable number. Our schemes support multiple properties including direction, distance, and time interval as well as a single property of direction, which is mainly used for modeling moving objects' trajectories. Finally, we show from our experiment that our schemes outperform Li's scheme(no-warping) and Shan's scheme(infinite-warping) in terns of precision and recall measures.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.102-112
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• 2000

The previous video structuring techniques are mainly limited to shot or shot group level. However, the shot level structure couldn't provide semantics within a video. So, researches on high level structuring are going on for getting over the drawbacks of shot level structure, recently. To overcome the drawbacks of shot level structure, we propose video scene segmentation technique based on color and motion features. For considering various color distribution, each shot is divided into sub-shots based on color feature. A key frame is extracted from each sub-shot. The motion feature in a shot is extracted from MPEG-1 video's motion vector. Moreover adaptive weights based on motion's property in search range are applied to color and motion features. The experiment results of proposed technique show the excellence in view of the over-segmentation and the reflection of semantics, comparing with those of previous techniques. The proposed technique decomposes video into meaningful hierarchical structure and provides video browsing or retrieval based on scene.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.31-42
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• 2002

In this paper, we propose a new spatio-temporal representation scheme which can model moving objets trajectories effectively in video data and a new signature-based access method for moving objects trajectories which can support efficient retrieval on user query based on moving objects trajectories. The proposed spatio-temporal representation scheme supports content-based retrieval based on moving objects trajectories and concept-based retrieval based on concepts(semantics) which are acquired through the location information of moving objects trajectories. Also, compared with the sequential search, our signature-based access method can improve retrieval performance by reducing a large number of disk accesses because it access disk using only retrieved candidate signatures after it first scans all signatures and performs filtering before accessing the data file. Finally, we show the experimental results that proposed scheme is superior to the Li and Shan's scheme in terns of both retrieval effectiveness and efficiency.

• 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.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.532-535
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• 2008

The requirement of Digital Culture Content(Movie, Music, Animation, Digital TV, Exhibition and etc.) is increasing so variety and quantity of content is also increasing. The Movie what majority of the digital Content is developing of technology and data. In the result, the efficient retrieval service has required and user want to use a recommendation engine and semantic retrieval methods through the recommendation system. Therefore, this paper will suggest analysing trait element of digital content data, building of retrieval technology, analysing and retrieval technology base on KANSEI vocabulary and etc. For the these, we made a extraction technology of trait element based on semantics and KANSEI processing algorithm based on color information.