• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.144-147
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• 2010

Recently the change of content consumption trend activated the social video sharing platform and the video clip itself. There have been intensive interests and efforts to automatically abstract compact and meaningful video clips. In this paper, we propose a method which use the clustering of the bookmark data created by collective intelligence instead of using the video content analysis. The partitional clustering of points in 2-dimensional space derived from the bookmark data make it possible to abstract highlights effectively. The method is enhanced by the 1-dimensional accumulated bookmark count graph. Experiments on the real data from KBS internet service show the effectiveness of the proposed method.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1564-1573
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• 2016

With the spread of social media and mobile devices, people spend more time on online than ever before. As more people participate in various online activities, much research has been conducted on how to make use of the time effectively and productively. In this paper, we propose two methods which can be used to extract highlights and make searchable media indexes using online social data. For highlight extraction, we collected the comments from the online baseball broadcasting website. We adopted peak-finding algorithm to analyze the frequency of comments uploaded on the comments section of the website. For each indexes, we collected postings from soap opera forums provided by a popular web service called DCInside. We extracted all the instances when a character's name is mentioned in postings users upload after watching TV, which can be used to create indexes when the character appears on screen for the given episode of the soap opera The evaluation results shows the possibility of the crowdsourcing-based media interaction for both highlight extraction and index building.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.441-443
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• 2011

본 논문은 오디오 특징 분석을 기반으로 한 음악검색 방법에 대한 기술과 연구에 대한 내용이다. 본 연구에서는 크게 3가지의 주요 알고리즘을 이용하여 다 성음에서의 오디오 특징을 추출하고 3가지의 각자 다른 방식의 매칭 알고리즘을 기반으로 한 퓨전 매칭 방식을 제안한다. 오디오 특징으로는 메인 멜로디, 음악 구조를 분석한 세그먼테이션 정보를 이용한다. 본 연구에서 사용된 음악 DB는 음악 포털 서비스에서 제공하는 장르를 기반으로 한 8가지 장르에서 다양한 범위에서 2000곡을 선곡하였다. 오디오 특징 추출을 위한 알고리즘 개발과 매칭 알고리즘 개발을 위하여 음악 DB 2000곡 중 장르의 비율을 고려하여 100곡을 선정하고, 24명으로부터 1200개의 허밍을 녹음하였다. 24명중 3명은 대학에서 음악을 전공하고 나머지는 음악적 교육을 받은 경험이 없는 사람들이다. 1200개의 허밍을 분석한 결과 전체 허밍 중 60%정도가 노래의 시작 부분을 허밍하거나 노래를 불렀고, 30%정도는 하이라이트 부분을 허밍 하였다. 나머지 10%정도는 자신이 가장 자신 있는 부분을 불렀다. 이러한 분석 결과를 기반으로 가장 중요한 부분은 노래가 시작되는 부분에서의 멜로디를 정확하게 찾아내는 것이 무엇보다 중요하다는 것이다. 본 연구에서 검색결과의 평가는 MRR를 이용하여 측정하였다. MIDI DB를 사용한 경우가 다 성음에서 직접 멜로디를 추출한 경우보다 약간 성능이 우수하게 나왔으나 그 차이는 미미했다. 본 연구에서는 개발된 알고리즘을 이용하여 PC상에서 사용할 수 있는 클라이언트 프로그램과 Android app를 개발하였다.

• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.396-405
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• 2001

Usually it is difficult to extract facial regions in a complex image by using only a predetermined skin color. Expecially, it is more difficult to separate them from background regions that contains the skin color. This paper proposes a face detection method by using gradual range expansion of an initial skin color. By analyzing the skin color distribution several images that are collected in the Web, the range of dense distribution is selected as the range of the initial skin color. In each expanding step, expanded regions in the image are tested whether they can be actual facial regions by using the information of the shape of general face and the location of face organs. The shape of general face is modeled as an ellipse and the aspect ratio of its bounding box is used to define the shape constraint for faces. Only the eyes and lips are used as the face organs, which can be easily detected by extracting horizontal edges in the expanded regions. through several experiments, it is confirmed that the proposed method can detect exactly not only faces having partly distorted regions by highlight but also faces neighboring similar color regions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.757-758
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• 2010

At the time of medical treatment and surgical operation, halogen lamp and plasma lamp were mainly used as luminous source for lighting. These two luminous sources have drawbacks that the life of lamps are not long, various problems are brought about due to excessive heat generation and its volume is very big because of cooling device. Accordingly, in this research a ring light was developed so that a partial shadowless shooting for the patient's affected area at the medical treatment room and surgical operation room using high luminance LED for which attention is being paid as new lighting parts for medical purpose. LED which was applied to the development used high luminance three color LED for full color for which various color materialization and the adjustment of radiation intensity are possible and we can get white light in order to emphasize the delicate expression for generic tone of shooting object, strong highlight, simple shadow and three dimensional effect at the time of close-up shadowless shooting of the affected area.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.89-98
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• 2007

For browsing, searching, and manipulating video documents, an indexing technique to describe video contents is required. Until now, the indexing process is mostly carried out by specialists who manually assign a few keywords to the video contents and thereby this work becomes an expensive and time consuming task. Therefore, automatic classification of video content is necessary. We propose a fully automatic and computationally efficient method for analysis and summarization of spots news video for 5 spots news video such as soccer, golf, baseball, basketball and volleyball. First of all, spots news videos are classified as anchor-person Shots, and the other shots are classified as news reports shots. Shot classification is based on image preprocessing and color features of the anchor-person shots. We then use the dominant color of the field and motion features for analysis of sports shots, Finally, sports shots are classified into five genre type. We achieved an overall average classification accuracy of 75% on sports news videos with 241 scenes. Therefore, the proposed method can be further used to search news video for individual sports news and sports highlights.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.82-93
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• 2000

Recently, the capability of efficient access to the desired video content is of growing importance because more digital video data are available at an increasing rate. A video summary abstracting the gist from the entirety enables the efficient browsing as well as the fast skimming of the video contents. In this paper, we discuss a novel dynamic summarization method based on the detection of highlights which represent semantically significant content and the description scheme (DS) proposed to MPEG-7 aiming to provide summary description. The summary DS proposed to MPEG-7 allows for efficient navigation and browsing to the contents of interest through the functionalities of multi-level highlights, hierarchical browsing and user-customized summarization. In this paper, we also show the validation and the usefulness of the methodology for dynamic summarization and the summary DS in real applications with soccer video sequences.

• The Journal of the Acoustical Society of Korea
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• v.33 no.3
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• pp.174-183
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• 2014

When a active sonar signal is transmitted and returned back from a target, it has been distorted by various properties of acoustic channel such as multipath arrivals. And signals have been appeared to be different form by target position and attitude. Therefore, we simulated the target echo signal using 3 dimensional target model include reflects target features. In this paper, we develop components form of a simulated target model is made up equally spaced highlight points, and each part of the target consists of shape function. We can simulate a target echo signal and Target strength (TS) according to wave incident angle. To verify, we made small scale target in kit form and we had got underwater target signal for comparing simulation result in water tank.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.197-217
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• 2011

Web accessibility refers to the practice of providing equal access to web sites to people without and with disability. This study aims to investigate the web content accessibility of 153 university libraries in Korea, and further suggest the approach to implement an effective university library web site to meet Korean Web Content Accessibility Guidelines(KWCAG). Survey was conducted with two steps. The first step was to find out the general level of web accessibility of all university library web sites using an automatic appraisal tool, KADO-WAH2.0, and the detailed examination of web accessibility check items was limited to 19 web sites which proved excellent in automatic appraisal. Regretfully, the result says that there is no perfect web site. Therefore every university library is advisable to make good use of the findings to meet all the requirements of KWCAG. In particular, the basic requirements, such as voice service, resizing and highlighting text, must be fulfilled by priority and to almost all contents.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.113-118
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• 2022

Motivated by people highlighting important phrases while reading or taking notes we propose a neural network training method by highlighting defective pixel areas to classify effectively defect types of images with complex background textures. To verify our proposed method we apply it to the problem of classifying the defect types of tire band fabric images that are too difficult to classify. In addition we propose a backlight highlighting technique which is tailored to the tire band fabric images. Backlight highlighting images can be generated by using both the GradCAM and simple image processing. In our experiment we demonstrated that the proposed highlighting method outperforms the traditional method in the view points of both classification accuracy and training speed. It achieved up to 13.4% accuracy improvement compared to the conventional method. We also showed that the backlight highlighting technique tailored for highlighting tire band fabric images is superior to a contour highlighting technique in terms of accuracy.