• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.219-232
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• 2005

With the rapid progress of computer technology in recent years, a digital video data has been used in many applications. As a result, various technologies have been introduced to discover knowledge embedded in a video database. However, few researches on data mining for a video database have been performed due to the unclear boundary of the information in a large amount of a video stream. This paper proposes an efficient generation method of a feature profile in a set of similar video data. To extract the information embedded in original video data efficiently, several refinement techniques are also presented. These methods include merging pixels, restricting preferred areas, removing noises under a minimum repeat factor, extracting important key frames, generating derived blocks and applying weights to dynamic and static areas differently. Finally, the performance of these methods is evaluated by comparing a result profile obtained by a data mining process with original video streams.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.64-73
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• 2012

In this paper, we propose a method to search for identical videos. The proposed method is spatio-temporal group feature fingerprinting. Frame of video is extracted from fixed rate method and is partitioned into vertical group and horizontal group. Descriptor is made of each group feature that is extracted from binary fingerprinting. Next, use descriptor of original video to build a two type of fingerprinting database and matching with query video. To efficient and effective video copy detection, method have high robustness, independence, matching speed. In proposed method, group feature have high robustness and independence in variable modification of video. Building a original fingerprinting database is able to fast matching with query video. The proposed method shows performance improvement in variable modifications in comparison to the existing methods. Especially, very singular performance in speed improvement is great advantage of this paper.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.99-105
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• 2000

Video has become an important element of multimedia computing and communication environments, with applications as varied as broadcasting, education, publishing, and military intelligence. The necessity of the efficient methods for multimedia data retrieval is increasing more and more on account of various large scale multimedia applications. According1y, the retrieval and representation of video data becomes one of the main research issues in video database. As for the representation of the video data there have been mainly two approaches: (1) content-based video retrieval, and (2) annotation-based video retrieval This paper designs and implements a video retrieval system for using semantic-based annotation.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.319-334
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• 1997

불과 2년 전만 하더라도 인터넷에서 오디오 또는 비디오 데이터를 감상하기까지 일련의 과정은 그 데이터의 물리적인 양과 전달방식에 있어서 이용자들에게 많은 인내력을 요구해 왔다. 이에 대한 해결책으로 관련업계에서는 real-time streaming 기술을 도입하여 각종 비디오와 오디오 데이터 전송에 관련기술을 적용시킴으로서 실시간 비디오/오디오 서비스 이용을 용이하게 하려는 움직임이 활발히 진행되어 왔었다.(중략)

• 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.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.20-29
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• 2010

The typical Kinetic Family Drawing (KFD) Web database system, a form of prototype system, has been developed, relying on the suggestions from family art therapists, with an aim to handle large amounts of assessment data and to facilitate effective implement of assessment activities. However, unfortunately such a system has an intrinsic problem that it fails to collect clients' behaviors, attitudes, facial expressions, voices, and other critical information observed while they are drawing. Accordingly we propose the ontology based video event analysis and video retrieval system in this paper, in order to enhance the function of a KFD Web database system by using a web camera and drawing tool. More specifically, a newly proposed system is designed to deliver two kinds of services: the client video retrieval service and the sketch video retrieval service, accompanied by a summary report of occurred events and dynamic behaviors relative to each family member object, respectively. The proposed system can support the reinforced KFD assessments by providing quantitative and subjective information on clients' working attitudes and behaviors, and KFD preparation processes.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.401-413
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• 2006

We propose video management system based on MPEG-7 for mobile device(MVMS). Most of existing MPEG-7 applications manage MPEG-7 document based on file system in the desktop environment. To contrast them, because the MVMS manages only necessary information using embedded database system for MPEG-7 documents in mobile devices, it can use efficiently lack of the resource in mobile device environment. MVMS supports key image extraction and MPEG-7 document edition function. Moreover, this is possible search and management of multi document because of MVMS manage MPEG-7 data through embedded DB.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.631-644
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• 2002

In this paper efficient algorithms for content-based video retrieval using motion information are proposed, including temporal scale-invariant retrieval and temporal scale-absolute retrieval. In temporal scale-invariant video retrieval, the distance transformation is performed on each trail image in database. Then, from a given que교 trail the pixel values along the query trail are added in each distance image to compute the average distance between the trails of query image and database image, since the intensity of each pixel in distance image represents the distance from that pixel to the nearest edge pixel. For temporal scale-absolute retrieval, a new coding scheme referred to as Motion Retrieval Code is proposed. This code is designed to represent object motions in the human visual sense so that the retrieval performance can be improved. The proposed coding scheme can also achieve a fast matching, since the similarity between two motion vectors can be computed by simple bit operations. The efficiencies of the proposed methods are shown by experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.892-911
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• 2019

Biometric recognition systems have been widely used for information security. Among the most popular biometric traits, there are fingerprint and face due to their high recognition accuracies. However, the security system that uses face recognition as the login method are vulnerable to face-spoofing attacks, from using printed photo or video of the valid user. In this study, we propose a fast and robust method to detect face-spoofing attacks based on the analysis of spatial frequency differences between the real and fake videos. We found that the effect of a spoofing attack stands out more prominently in certain regions of the 2D Fourier spectra and, therefore, it is adequate to use the information about those regions to classify the input video or image as real or fake. We adopt a divide-conquer-aggregate approach, where we first divide the frequency domain image into local blocks, classify each local block independently, and then aggregate all the classification results by the weighted-sum approach. The effectiveness of the methodology is demonstrated using two different publicly available databases, namely: 1) Replay Attack Database and 2) CASIA-Face Anti-Spoofing Database. Experimental results show that the proposed method provides state-of-the-art performance by processing fewer frames of each video.