• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.61-68
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• 2016

In this paper, an implementation method of augmented reality (AR) technology using Web 3.0 information services in the field of disaster response is proposed. The structure and characteristics of semantic web-based Web 3.0 are realized and a AR based mobile visual search (MVS) applied in the disaster sites is described. Based on Web 3.0 and AR MVS, a semantic web ontology oriented configuration scheme for disaster-related information and the communication scheme of information provided by AR technology are proposed. For the purpose of providing disaster-related and customized information to the disaster response site quickly and accurately, a method of leveraging Web 3.0 information services in AR technology is presented.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.731-740
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• 2015

Mobile (smartphone) search engine marketing is increasingly important. Accordingly, the development of visual apparel search technology to obtain easier and faster access to visual information in the apparel field is urgently needed. This study helps establish a proper classifying system for an apparel search after an analysis of search techniques for apparel search applications and existing domestic and overseas apparel sites. An annotation technique is developed in accordance with visual attributes and apparel categories based on collected data obtained by web crawling and apparel images collecting. The categorical composition of apparel is divided into wearing, image and style. The web evaluation site traces the correlations of the apparel category and apparel factors as dependent upon visual attributes. An appraisal team of 10 individuals evaluated 2860 pieces of merchandise images. Data analysis consisted of correlations between apparel, sleeve length and apparel category (based on an average analysis), and correlation between fastener and apparel category (based on an average analysis). The study results can be considered as an epoch-making mobile apparel search system that can contribute to enhancing consumer convenience since it enables an effective search of type, price, distributor, and apparel image by a mobile photographing of the wearing state.

• Journal of Information Management
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• v.40 no.2
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• pp.71-94
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• 2009

Indexing images using traditional indexing methods like taxonomy is not always efficient because of its visual content. This study examined how to apply folksonomies to image retrieval. To do this, first, we developed a category model for image tags found in Flickr. The model includes five categories and seventeen subcategories. Second, in order to evaluate the usefulness of the model to represent the various image tags as well as to investigate the end-user tagging behavior, three researchers classified the sampled image tags(141 most popular tags, 105 tags on three individual tag clouds and 3,848 image tags assigned on 156 images) according to the model. Finally, based on the research results, we proposed three methods for efficient image retrieval: extending folksonomies by combining them with ontologies; improving image retrieval efficiency using visual content and folksonomies; and updating taxonomy using folksonomies.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.383-393
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• 2005

Retrieval of images from image databases by spatial relationship can be effectively performed through visual interface systems. In these systems, the representation of image with 2D strings, which are derived from symbolic projections, provides an efficient and natural way to construct image index and is also an ideal representation for the visual query. With this approach, retrieval is reduced to matching two symbolic strings. However, using 2D-string representations, spatial relationships between the objects in the image might not be exactly specified. Ambiguities arise for the retrieval of images of 3D scenes. In order to remove ambiguous description of object spatial relationships, in this paper, images are referred by considering spatial relationships using the spatial location algebra for the 3D image scene. Also, we remove the repetitive spatial relationships using the several reduction rules. A reduction mechanism using these rules can be used in query processing systems that retrieve images by content. This could give better precision and flexibility in image retrieval.

• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.18-23
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• 2004

In this paper, we propose a new visual feature extraction method for content-based image retrieval(CBIR) based on wavelet transform which has both spatial-frequency characteristic and multi-resolution characteristic. We extract visual features for each frequency band in wavelet transformation and use them to CBIR. The lowest frequency band involves spacial information of original image. We extract L feature vectors using fuzzy homogeneity in the wavelet domain, which consider both the wavelet coefficients and the spacial information of each coefficient. Also, we extract 3 feature vectors wing the energy values of high frequency bands, and store those to image database. As a query, we retrieve the most similar image from image database according to the 10 largest homograms(normalized fuzzy homogeneity vectors) and 3 energy values. Simulation results show that the proposed method has good accuracy in image retrieval using 90 texture images.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• Journal of The Korean Association of Information Education
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• v.9 no.4
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• pp.595-606
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• 2005

7차교육과정에서의 초등 컴퓨터교육은 재량활동시간 또는 특별활동시간에 단순한 응용프로그램(워드프로세서, 엑셀, 파워포인트 등)을 활용하거나 인터넷을 이용한 정보검색 수준이다. 따라서, 문제해결 능력이나 논리적 사고력을 향상시키는데는 미흡하다. 인지능력이 뛰어난 초등학교 5, 6학년에는 이러한 컴퓨터 활용방법 교육보다 컴퓨터 기초원리 또는 프로그래밍교육이 필요하다. 본 논문은 프로그래밍교육을 재량 특별활동 시간에 학년별(5, 6학년) 또는 통합학년으로 학습할 수 있게 프로그래밍교육과정 60차시 분을 개발하여 제안하였다. 개발한 교육과정은 교수 및 학습자의 요구사항을 최대한 반영하기 위해 설문조사 등을 통해 얻은 기초자료를 참조하였다. 제안한 교육과정이 초등학교 5, 6학년에 적합하고 우수한지를 검토하기 위해 일부 차시의 교육과정으로 5, 6학년을 대상으로 재량활동시간에 직접 교수 학습한 후 자기평가, 설문조사를 실시하였다. 결과로 제안한 교육과정이 적합성과 우수성이 있다고 판단되었다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.513-518
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• 2010

The advancement of information technology along with the proliferation of communication and multimedia has increased the demand of digital contents. Video data of digital contents such as VOD, NOD, Digital Library, IPTV, and UCC are getting more permeated in various application fields. Video data have sequential characteristic besides providing the spatial and temporal information in its 3D format, making searching or browsing ineffective due to long turnaround time. In this paper, we suggest ATVC(Authoring Tool for Video Contents) for solving this issue. ATVC is a video editing tool that detects key frames using visual rhythm and insert metadata such as keywords into key frames via XML tagging. Visual rhythm is applied to map 3D spatial and temporal information to 2D information. Its processing speed is fast because it can get pixel information without IDCT, and it can classify edit-effects such as cut, wipe, and dissolve. Since XML data save key frame information via XML tag and keyword information, it can furnish efficient browsing.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.96-106
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• 2002

We introduce a novel scheme to characterize and index events in TV golf programs using MPEG-7 descriptors. Our goal is to identify and localize the golf events of interest to facilitate highlight-based video indexing and summarization. In particular, we analyze multiple (low-level) visual features using domain-specific model to create a perceptual relation for semantically meaningful(high-level) event identification. Furthermore, we summarize a TV golf program with TV-Anytime segmentation metadata, a standard form of an XML-based metadata description, in which the golf events are represented by temporally localized segments and segment groups of highlights. Experimental results show that our proposed technique provides reasonable performance for identifying a variety of golf events.