• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.729-732
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• 2000

대용량 비디오 데이터의 이용에 있어 효과적인 비디오 검색을 위해서는 비디오 데이터의 색인 과정이 필요하다. 효과적인 비디오 데이터의 색인을 위해서는 의미적 단위인 씬(Scene)으로 이루어진 비디오 데이터를 물리적인 경계면인 컷(장면전환점)으로 검출하는 기법이 필수적이며 각 샷에서의 키 프레임 추출 또한 필수적이다. 본 논문에서는 뉴스 비디오데이터의 키 프레임인 앵커 프레임의 효과적인 검색을 위해 DC 성분 추출과 이진 검색기법, 그리고 컬러 클러스터링을 이용하고 있다. 본 논문에서 제하고 있는 방법을 검증하기 위해서 47분 10초 분량의 MPEG-2 로 압축된 뉴스 비디오 데이터에 적용한 결과 91.3%의 정확도와 84.0%의 재현율을 보여 제안한 방법의 우수성을 증명하고 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.239-242
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• 2000

급속한 컴퓨터 및 통신 기술의 발전으로 인해 동영상 정보는 인터넷 및 사회전반의 다양한 분야들에서 활용되고, 기하급수적으로 증가되고 있으나, 기존의 정보 분석 시스템은 기본적으로 텍스트를 기반으로 한 것이기에, 동영상 정보가 가지는 애매성을 표현하기 곤란하며, 주석 작성에 따르는 과다한 작업부담 및 객관성 결여들의 문제점을 가지고 있다. 이에, 상기에 기술한 문제점을 해결하기 위하여 대용량의 동영상 정보를 효율적으로 분석 할 수 있는 동영상 분석 알고리즘을 제안하고자 한다. 본 논문의 주된 연구과제는 컷 검출을 위한 통합 특징량 적용법과 색상특징, 모양특징을 사용하여 이미지 내의 특징 정보를 분석하는 것이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.141-148
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• 2011

Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.379-386
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• 2004

Video segmentation is a fundamental task in video indexing and it includes two kinds of shot change detections such as the abrupt transition and the gradual transition. The abrupt shot boundaries are detected by computing the image-based distance between adjacent frames and comparing this distance with a pre-determined threshold value. However, the gradual shot boundaries are difficult to detect with this approach. To overcome this difficulty, we propose the method that detects gradual transition in the MPEG compressed video using the HMM (Hidden Markov Model). We take two different HMMs such as a discrete HMM and a continuous HMM with a Gaussian mixture model. As image features for HMM's observations, we use two distinct features such as the difference of histogram of DC images between two adjacent frames and the difference of each individual macroblock's deviations at the corresponding macroblock's between two adjacent frames, where deviation means an arithmetic difference of each macroblock's DC value from the mean of DC values in the given frame. Furthermore, we obtain the DC sequences of P and B frame by the first order approximation for a fast and effective computation. Experiment results show that we obtain the best detection and classification performance of gradual transitions when a continuous HMM with one Gaussian model is taken and two image features are used together.

• Journal of the Korea Society of Computer and Information
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• v.3 no.4
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• pp.27-34
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• 1998

In this paper we present a method for automatic motion vector and brightness based video indexing and retrieval. We extract a representational frame from each shot and compute some motion vector and brightness based features. For each R-frame we compute the optical flow field; motion vector features are then derived from this flow field, BMA(block matching algorithm) is used to find motion vectors and Brightness features are related to the cut detection of method brightness histogram. A video database provided contents based access to video. This is achieved by organizing or indexing video data based on some set of features. In this paper the index of features is based on a B+ search tree. It consists of internal and leaf nodes stores in a direct access a storage device. This paper defines the problem of video indexing based on video data models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5902-5909
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• 2011

In this paper, we propose a new method to detect abrupt and gradual shot transitions of video data by using certainty factors. The abrupt transitions denotes cuts and the gradual transitions fade in, fade out, dissolve, horizontal wipes, vertical wipes, Barn Doors, and Iris Rounds. The suggested method first extracts representative features for each shot transition and determines corresponding shot transitions by integrating all the extracted features and inferring adequate transitions. To verify the performance of the proposed shot transition method, experimental results show that the suggested method can detect shot transitions more accurately than existing methods.

• Journal of Game and Entertainment
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• v.2 no.2
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• pp.51-60
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• 2006

Recently, many streaming videos including drama, music videos, and movies have been extensively given on the web. Such video services are on negative lines in any service restriction depending on the age of users and then whole part of a video have been restricted considering the age of users. Therefore, in this paper, we will present a new method that provides the access depending on the ages of users and also sets the video rating of each scene in a video. To get this restricted access for video, we will first divide a streaming video into many scenes using histogram techniques. Each scene gets an access control depending on the nudity level. Finally, we will make the video indexing including the access level depending on its nudity level and then hide restricted scenes using several masks in playing that streaming video.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.4
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• pp.287-293
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• 2005

Ultrasonic guided waves are gaining increasing attention for the inspection of platelike and rodlike structures. At the same time, inspection methods that do not require contact with the test piece are being developed for advanced applications. This paper capitalizes on recent advances in the areas of guided wave ultrasonics and noncontact ultrasonics to demonstrate a superior method for the nondestructive detection of defects thinning simulating hidden corrosion in thin aluminum plates. The proposed approach uses EMAT(electro-magnetic acoustic transducer) for the noncontact generation and detection of guided waves. Interesting features in the dispersive behavior of selected guided modes are used for the detection of plate thinning. It is shown that mode cutoff measurements provide a qualitative detection of defects thinning. Measurement of the mode group velocity can be also used to quantify depth thinning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.786-795
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• 2002

In this paper, we present a histogram and moment-based vidoe scencd change detection technique using hierarchical Hidden Markov Models(HMMs). The proposed method extracts histograms from a low-frequency subband and moments of edge components from high-frequency subbands of wavelet transformed images. Then each HMM is trained by using histogram difference and directional moment difference, respectively, extracted from manually labeled video. The video segmentation process consists of two steps. A histogram-based HMM is first used to segment the input video sequence into three categories: shot, cut, gradual scene changes. In the second stage, a moment-based HMM is used to further segment the gradual changes into a fade and a dissolve. The experimental results show that the proposed technique is more effective in partitioning video frames than the previous threshold-based methods.

• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.201-209
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• 2000

Recent works regarding video shot change detection algorithms show that abrupt shot changes are detected fairly well. However, gradual shot changes including wipes and dissolves are often missed or falsely detected. A robust shot change detection system, therefore, must include a shot verification step to further enhance the overall system performance. In this paper, we introduce the concept of the visual rhythm which is a single image, a subsampled version of a full video. On the visual rhythm, the different video edit effects such as cuts, wipes and dissolves manifest themselves as different patterns. Using this characteristic, it becomes possible, without sequentially playing the entire video, to find false positive shots as well as undetected shots. Thus, inclusion of the visual rhythm in the shot boundary verification process will aid the operator to exclude falsely detected shots as well as to find undetected shots fast and efficiently. For this purpose we have developed a new tool, a shot verifier incorporating the visual rhythm. The usefulness of the visual rhythm during the shot verification process will be presented.