• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.7-14
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• 2006

This paper presents an efficient face recognition method using both first moment of image and basis images. First moment which is a method for finding centroid of image, is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. Basis images which are the face features, are respectively extracted by principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). This is to improve the recognition performance by excluding the redundancy considering to second- and higher-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 48 face images(12 persons*4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed methods has a superior recognition performances(speed, rate) than conventional PCA and FP-ICA without preprocessing, the proposed FP-ICA has also better performance than the proposed PCA. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.33-40
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• 2006

This paper presents an efficient face recognition method using both first moment of image and eigenvector. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shitting to the centroid of face image. Eigenvector which are the basis images as face features, is extracted by principal component analysis(PCA). This is to improve the recognition performance by excluding the redundancy considering to second-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 60 face images(15 persons *4 scenes) of 320*243 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. In case of the 45 face images, the experimental results show that the recognition rate of the proposed methods is about 1.6 times and its the classification is about 5.6 times higher than conventional PCA without preprocessing. The city-block has been relatively achieved more an accurate classification than Euclidean or negative angle.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.265-271
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• 2019

The number of galleries across the country is increasing as interest in cultural life increases due to the increase in national income. However, museum satisfaction is relatively low compared to other services. In this paper, we propose a service that provides preference information based on machine learning in embedded system environment in order to increase museum satisfaction. The proposed algorithm implements an embedded system using Raspberry Pi. Machine learning was used to find works similar to the viewer's favorite works, and several models were compared to select models applicable to embedded systems. By using the preference information, it is possible to effectively organize the gallery exhibition contents to increase the exhibition satisfaction and the re-visit rate of the museum.

• Information Systems Review
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• v.22 no.2
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• pp.167-199
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• 2020

The ICT-based curation as a series of experiences with the mobile exhibition-guide applications or guide programs in art galleries helps visitors fully immersed in the exhibition and allows them to have more informative and convenient guide experience at art galleries. This study aims to verify how the factors of ICT-based curation affects the commitment and satisfaction of visitors at art galleries, figure out whether the visitors' commitment has effects on their satisfaction, and then finally test the impact of their commitment and satisfaction on their revisit intention. In order to validate the cause-and-effect relationships between these factors, the ICT-based curation in this paper is categorized into five factors - gamification, quality of image/video information, quality of sound/text information, contextual offer, and instant connectivity. The main results of the study are as follows. First, only the gamification has significantly positive effects on the commitment of art gallery visitors, while other two factors - the instant connectivity, and the quality of sound/text information - have significantly positive effects on the satisfaction of visitors. Second, the commitment of visitors also has significantly positive effects on their satisfaction. Third, the commitment of the visitors don't have significantly positive relationship with their intention of revisit, but the satisfaction of the visitors have significantly positive relationship with their intention of revisit.

• Korean Institute of Interior Design Journal
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• v.23 no.1
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• pp.78-87
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• 2014

The purpose of this paper is to analyze the relationship between panoramic perception and space organization for restoration of urban environment and architecture. Panorama is a collective visual catalogue composed by series of perspective images. It is a product from continuous movements of viewer by defamilarizing real image and structuring order between city and building. Through understanding the panoramic image, the viewer is able to achieve the total image of the city. For example, achieving visual perception of the city by employing the panoramic view from different historical backgrounds and cultures, Berlin developed its urban characteristic by rebuilding panoramic view as an aesthetic device. First, this paper mention theory of panorama as an aesthetic device for shaping the city from the building. Second, this paper analyze the relationships between characteristics of panorama and historical contexts for why those panoramic views are valuable by mentioning the Altes Museum, the Berlin National Gallery, Museum of Modern Literature, and Folkwang Museum of panoramic view. In conclusion, this paper argues that visual perception such as panoramic view is the valuable device for organizing the image of the city's own identity. Constructing vision of each city influences not only shaping the city but also mapping the mental views of the building. Also, historical conditions and open spaces are one of the inherent elements combined with panoramic view for establishing urban identity. In search for good place making, it is important to understand the role of the historical context and fabric plan in shaping how a resident sees - literally, sees- their city with buildings. Berlin serve as excellent counter example in how the valuable place making panoramic mental views of urbanities take shape.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.368-391
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• 2018

Face recognition (FR) with a single sample per person (SSPP) is common in real-world face recognition applications. In this scenario, it is hard to predict intra-class variations of query samples by gallery samples due to the lack of sufficient training samples. Inspired by the fact that similar faces have similar intra-class variations, we propose a virtual sample generating algorithm called k nearest neighbors based virtual sample generating (kNNVSG) to enrich intra-class variation information for training samples. Furthermore, in order to use the intra-class variation information of the virtual samples generated by kNNVSG algorithm, we propose image set based multimanifold discriminant learning (ISMMDL) algorithm. For ISMMDL algorithm, it learns a projection matrix for each manifold modeled by the local patches of the images of each class, which aims to minimize the margins of intra-manifold and maximize the margins of inter-manifold simultaneously in low-dimensional feature space. Finally, by comprehensively using kNNVSG and ISMMDL algorithms, we propose k nearest neighbor virtual image set based multimanifold discriminant learning (kNNMMDL) approach for single sample face recognition (SSFR) tasks. Experimental results on AR, Multi-PIE and LFW face datasets demonstrate that our approach has promising abilities for SSFR with expression, illumination and disguise variations.

• Fashion & Textile Research Journal
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• v.1 no.2
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• pp.119-126
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• 1999

The purpose of this study was to serve as a basis for the creation of new design. For attaining the purpose, an investigation was made into the actual condition or problems of domestic and foreign fashion design, and fashion design information was acquired from the Internet. Then, taking the acquired information as the basic data for merchandising, an attempt was made to work out an outline by using the Corel-Trace program, a widely-used computer software, and to modify it by using the Corel-Draw program. The findings of this study were as below: 1) The informations provided by domestic home-pages were largely made up of fashion news and articles on the trend of fashion, but included few of picture report. Almost all of them weren't developed into a database by item or detail. The foreign fashion design web-site were numerous in number, providing diverse information. They offered not only moving images or picture report on fashion show, leading models, photo gallery or fashion trend, but up-dated data everyday. 2) A way to create a design to meet a designer's target is recommended in this study. At first, the fashion information acquired through computer network would be handled by the Corel-Trace program. After Bitmap image would be converted into Vector image, that would be modified by the Corel-Draw program to create a design to suit a designer's target.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3144-3164
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• 2019

Face recognition systems have several potential applications, such as security and biometric access control. Ongoing research is focused to develop a robust face recognition algorithm that can mimic the human vision system. Face pose, non-uniform illuminations, and low-resolution are main factors that influence the performance of face recognition algorithms. This paper proposes a novel method to handle the aforementioned aspects. Proposed face recognition algorithm initially uses 68 points to locate a face in the input image and later partially uses the PCA to extract mean image. Meanwhile, the AdaBoost and the LDA are used to extract face features. In final stage, classic nearest centre classifier is used for face classification. Proposed method outperforms recent state-of-the-art face recognition algorithms by producing high recognition rate and yields much lower error rate for a very challenging situation, such as when only frontal ($0^{\circ}$) face sample is available in gallery and seven poses ($0^{\circ}$, ${\pm}30^{\circ}$, ${\pm}35^{\circ}$, and ${\pm}45^{\circ}$) as a probe on the LFW and the CMU Multi-PIE databases.

• Journal of the Korean Society of Industry Convergence
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• v.8 no.4
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• pp.221-226
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• 2005

This paper presents a hybrid method for recognizing the faces by using zero mean and principal component analysis. Zero mean is applied to reduce the 1st order statistics to data nonlinearities. PCA is also used to derive an orthonormal basis which directly leads to dimensionality reduction, and possibly to feature extraction of face image. The proposed method has been applied to the problems for recognizing the 20 face images(10 persons * 2 scenes) of 324*243 pixels from Yale face database. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.253-255
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• 2003

기존의 개념 기반 이미지 검색에서는 이미지의 의미적 내용 인식을 위해 일반적으로 어휘적 정보나 텍스트 정보를 이용했다. 이러한 텍스트 정보 기반 이미지 검색은 전통적인 검색 방법인 키워드 검색 기술을 그대로 사용하여 쉽게 구현할 수 있으나 텍스트의 개념적 매칭이 아닌 스트링 매칭이므로 주석처리된 단어와 정확한 매칭이 없다면 찾을 수가 없었다. 이에 본 논문에서는 ontology의 일종인 WordNet을 이용하여 깊이 정보량 링크 타입, 밀도 등을 고려한 개념간 유사성 측정으로 패턴 매칭의 문제를 해결하고자 했다. 또한 키워드로 주석처리 되어 있는 Microsofts Design Gallery Live의 이미지를 이용하여 개념간 유사성 측정법을 실질적으로 개념 기반 이미지 검색에 적용해 보았다.