• 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.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.297-300
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• 2000

본 논문에서는 MPEG 비디오 스트림을 분석하여 DCT DC 계수를 추출하고 이들로 구성된 DC 이미지로부터 제안하는 robust feature를 이용하여 shot을 구하고 각 feature들의 통계적 특성을 이용하여 스트림의 특징에 따라 weight를 부가하여 구해진 characterizing value의 시간변화량을 구한다. 구해진 변화량의 local maxima와 local minima는 MPEG 비디오 스트림에서 각각 가장 특징적인 frame과 평균적인 frame을 나타낸다. 이 순간의 frame을 구함으로서 효과적이고 빠른 시간 내에 key frame을 추출한다. 추출되어진 key frame에 대하여 원영상을 복원한 후, 색인을 위하여 다수의 parameter를 구하고 사용자가 질의한 영상에 대해서 이들 파라메터를 구하여 key frame들과 가장 유사한 대표영상들을 검색한다.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.132-135
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• 2009

The video similarity measure is very important factor to index and to retrieve for video data. In this paper, we propose the luminance projection model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient measure using the luminance projection. To index effectively the video sequences and to decrease the computational complexity, we calculate video similarity using the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed luminance projection model yields the remarkable accuracy and performance than the conventional algorithm.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.47-56
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• 2005

A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.646-654
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• 2007

In recent years, the use of text inserted into TV contents has grown to provide viewers with better visual understanding. In this paper, video text is defined as superimposed text region located of the bottom of video. Video text extraction is the first step for video information retrieval and video indexing. Most of video text detection and extraction methods in the previous work are based on text color, contrast between text and background, edge, character filter, and so on. However, the video text extraction has big problems due to low resolution of video and complex background. To solve these problems, we propose a method to extract text from videos using the Harris corner detector. The proposed algorithm consists of four steps: corer map generation using the Harris corner detector, extraction of text candidates considering density of comers, text region determination using labeling, and post-processing. The proposed algorithm is language independent and can be applied to texts with various colors. Text region update between frames is also exploited to reduce the processing time. Experiments are performed on diverse videos to confirm the efficiency of the proposed method.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3333-3340
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• 2000

Recently, Requnremeni for video data have been increased rapidly by high progress of both hardware and cornpression technique. Because digital video data are unformed and mass capacity, it needs various retrieval techniquesjust as contednt-based rehieval Superimposed-caption ina digital video can help us to analyze the video story easier and be used as indexing information for many retrieval techniques In this research we propose a new method that segments the caption as analyzing texture eature of caption regions in each video frame, and that extracts the accurate scope of superimposed-caption frame and its key regions and color by measunng cominuity of caption regions between frames

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.235-247
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• 2002

For an efficient indexing and retrieval of digital video data, research on video caption extraction and recognition is required. This paper proposes methods for extracting artificial captions from video data and enhancing their image quality for an accurate Hangul and English character recognition. In the proposed methods, we first find locations of beginning and ending frames of the same caption contents and combine those multiple frames in each group by logical operation to remove background noises. During this process an evaluation is performed for detecting the integrated results with different caption images. After the multiple video frames are integrated, four different image enhancement techniques are applied to the image: resolution enhancement, contrast enhancement, stroke-based binarization, and morphological smoothing operations. By applying these operations to the video frames we can even improve the image quality of phonemes with complex strokes. Finding the beginning and ending locations of the frames with the same caption contents can be effectively used for the digital video indexing and browsing. We have tested the proposed methods with the video caption images containing both Hangul and English characters from cinema, and obtained the improved results of the character recognition.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.75-94
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• 2010

This study designed a pilot system in which queries can be expanded through a tag ontology where equivalent, synonymous, or related tags are bound together, in order to improve the retrieval effectiveness of videos. We evaluated the proposed pilot system by comparing it to a tag-based system without tag control, in terms of recall and precision rates. Our study results showed that the mean recall rate in the structured folksonomy-based system was statistically higher than that in the tag-based system. On the other hand, the mean precision rate in the structured folksonomy-based system was not statistically higher than that in the tag-based system. The result of this study can be utilized as a guide on how to effectively use tags as social metadata of digital video libraries.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.340-342
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• 2012

사람관련 사건을 실시간으로 인지하거나 빠르게 사건 관련 증거를 확보하기 위해서는 대량의 비디오 감시 데이터로부터 사람 관련 정보를 빠르게 찾을 수 있어야 하는데 기존의 시스템에서는 모든 프레임으로부터 주석 편집자가 수작업으로 관련 정보를 추출하여 색인해야 하기 때문에 많은 주석 시간을 필요로 하는 문제를 갖고 있었다. 본 논문에서는 대량의 방범용 비디오 감시 데이터로부터 사람 관련 사건 정보를 빠르게 찾을 수 있도록 지원하기 위해 전체 비디오 데이터 중에서 사람의 출현과 퇴장을 기준으로 키 프레임 구간을 추출하고, 키 프레임에서만 사람 관련 정보를 추출하여 사람 관련 주요 정보를 자동으로 추출하여 XML 스키마 형식으로 색인하는 비디오 주석 시스템을 개발하였다. 또한, 색인된 XML 데이터에 대해 구조 및 내용 기반 질의를 이용하여 쉽고 빠르게 검색할 수 있도록 하기 위해 XPATH 질의 인터페이스를 구현 하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1713-1720
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• 1999

This paper presents a new key frame extraction technique, for scene change detection, using the proposed AHIM (Accumulative Histogram Intersection Measure) from the DC image constructed by DCT DC coefficients in the compressed video sequence that is video compression standard such as MPEG. For fast content-based browsing and video retrieval in a video database, we also provide a novel coarse-to-fine video indexing scheme. In the extracted key frame, we perform the region segmentation as a preprocessing. First, the segmented image is projected with the horizontal direction, then we transform the result into a histogram, which is saved as a database index. In the second step, we calculate the moments and change them into a distance value. From the simulation results, the proposed method clearly shows the validity and superiority in respect of computation time and memory space, and that in conjunction with other techniques for indexing, such as color, can provide a powerful framework for image indexing and retrieval.