• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2355-2358
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• 2003

The purpose of this paper is to investigate two major feature extraction techniques based on generic modular face recognition system. Detailed algorithms are described for principal component analysis (PCA) and independent component analysis (ICA). PCA and ICA ate statistical techniques for feature extraction and their incorporation into a face recognition system requires numerous design decisions. We explicitly state the design decisions by introducing a modular-based face recognition system since some of these decision are not documented in the literature. We explored different implementations of each module, and evaluate the statistical feature extraction algorithms based on the FERET performance evaluation protocol (the de facto standard method for evaluating face recognition algorithms). In this paper, we perform two experiments. In the first experiment, we report performance results on the FERET database based on PCA. In the second experiment, we examine performance variations based on ICA feature extraction algorithm. The experimental results are reported using four different categories of image sets including front, lighting, and duplicate images.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.399-406
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• 2021

It is a key issue in the tunnel design to evaluate the stability of the excavation face. Two efficient analytical models in the context of the limit equilibrium method (LEM) and the limit analysis method (LAM) are used to carry out the deterministic calculations of the safety factor. The safety factor obtained by these two models agrees well with that provided by the numerical modelling by FLAC 3D, but consuming less time. A simple probabilistic approach based on the Mote-Carlo Simulation technique which can quickly calculate the probability distribution of the safety factor was used to perform the probabilistic analysis on the tunnel face stability. Both the cumulative probabilistic distribution and the probability density function in terms of the safety factor were obtained. The obtained results show the effectiveness of this probabilistic approach in the tunnel design.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.10-28
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• 2022

In this paper, we present an entry-level COVID-19 stand-alone digitial signage player (CoSiP) which performs not only conventional digital signage functionalities but also fever detection, face mask wearing detection, and KI-pass QR code checking. The overall design of CoSiP is proposed, and implementation of a temperature checking algorithm using a low cost thermal sensor is elaborately presented. Through experiments over datasets and against a developed CoSiP device, it is shown that the fever detection, face mask wearing detection, KI-pass QR code checking as well as signage functionalities of the proposed CoSiP work properly and reliably.

• The Journal of Industrial Distribution & Business
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• v.12 no.11
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• pp.17-31
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• 2021

Purpose: Despite the fact that face (i.e. Chemyon) is deeply-rooted in Korean culture and significantly affects the behavior of Korean people, the effect of face on leisure consumers' consumption behavior has only reported mixed findings, that is, significant and/or insignificant face effects have been reported. It is necessary to integrate prior research findings, and comprehensively examine the effect of face on leisure consumers' consumption behavior. The purpose of this study was to investigate the effect (i.e. effect size, and moderating variables) of face on leisure consumers' consumption behavior through meta-analysis. Research design, data and methodology: Among 1,019 face-related academic studies, retrieved from the academic research information services (RISS), 34 studies and 300 cases examining the effect of face on leisure consumers' consumption behavior were finally included for meta-analysis. Face measured as face sensitivity and/or a face sensitivity sub-component (shame-consciousness, formality-consciousness, and other-consciousness) were integrated in the meta-analysis. Leisure consumers' consumption behavior was classified as antecedents of purchase (overall conspicuous consumption tendency, overall symbolic consumption tendency, personality, high price, high quality, brand seeking, fashion seeking, enjoyment, other person (interpersonal) consideration, position, reference group, and attitude), purchase (purchase intention, unplanned purchase, purchase, and expenditure), and post-purchase (satisfaction, repurchase, and post-purchase). The data used in the meta-analysis was comprised of correlation coefficients, and the meta-analysis was performed using the R-program. Results: The overall mean effect size of face on leisure consumers' consumption behavior was .248. It was found that the effect size was the largest in the order of shame-consciousness face, formality-consciousness face, and other-consciousness face. Among the types of leisure consumers' consumption behavior categorized as dependent variables, the effect size was found to be largest in the order of position, attitude, reference group, post-purchase behavior, brand seeking, personality, trend seeking, etc. In addition, it was found that the leisure types moderated the effect size of face on leisure consumers' consumption behavior. The effect size was found to be largest in the order of skin diving, baseball, various leisure participation, dance, gambling, golf, etc. Conclusions: Face moderately or significantly influence leisure consumers' consumption behavior.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.193-200
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• 1999

Since Broms and Bennermark(1967) suggested the face stability criterion based on laboratory extrusion tests and field observations, the face stability of a tunnel driven in cohesive material has been studied by several authors. And recently, more general solution for the tunnel front is given by Leca and Panet(1988). They adopted a limit state design concept to evaluate the face stability of a shallow tunnel driven into cohesionless material and showed that the calculated upper bound solution represented the actual behavior reasonably well. In this study, two factors are simultaneously considered for assessing tunnel face stability: One is the effective stress acting on the tunnel front calculated by upper bound solution; and the other is the seepage force calculated by numerical analysis under the condition of steady state ground water flow. The model tests were performed to evaluate the seepage force acting on the tunnel front and these results were compared with results of numerical analysis. Consequently, the methodology to evaluate the stability of a tunnel face including limit analysis and seepage analysis is suggested under the condition of steady state ground water flow.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.24-31
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• 2017

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.161-170
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• 2010

This paper provides a novel approach for a user oriented system for face detection system for application developers. Even though there are many open source or commercial libraries to solve the problem of face detection, they are still hard to use because they require specific knowledge on detail algorithmic techniques. The purpose of this paper is to come up with a high-level system for face detection with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions so that application developers can use them to express various problems. Once the conditions are expressed by developers, the interpreter proposed take the role to interpret the conditions, find and organize the optimal algorithms to solve the represented problem with corresponding conditions. A proof-of-concept is implemented and some example problems are tested and analyzed to show the ease of use and usability.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.4
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• pp.189-203
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• 2014

In this study, Creative motifs using face composition of Jogakbo and Knot Symbol were developed, and applied to traditional Baeja of Joseon Dynasty to develop design contents of traditional clothes. As for study method, 7 motifs of new formative image that integrates traditional beauty and contemporary sense were developed by applying Knot Symbols and face compositions of Jogakbo with the use of Adobe Illustrator CS6 and Adobe Photoshop CS6 vector graphic software. The motifs were designed in contemporary image in face compositions like rectangle pattern, triangle pattern, dual rectangle pattern, vertical and horizontal pattern, pinwheel pattern, gojunmun pattern and free pattern by involving various changes like repetition, rotation, reduction, expansion and decomposition and using the colors used in the Jogakbo. It is desired that through this study, traditional Baeja may develop to bear traditional and contemporary image so that our traditional clothes design may become global. Also it is anticipated that this study will contribute to development of culture products of Hanbok like Jeogori, pants and skirt that require change of design in the global era while maintaining traditional beauty to appeal to the emotions of world citizens.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.353-362
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• 2005

Recently, study of Bimodal recognition has become very active. In this paper we propose a Bimodal user recognition system that uses face information and audio information. Face recognition consists of face detection step and face recognition step. Face detection uses AdaBoost to find face candidate area. After finding face candidates, PCA feature extraction is applied to decrease the dimension of feature vector. And then, SVM classifiers are used to detect and recognize face. Audio recognition uses MFCC for audio feature extraction and HMM is used for audio recognition. Experimental results show that the Bimodal recognition can improve the user recognition rate much more than audio only recognition, especially in the Presence of noise.