• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.592-595
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• 2009

In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.48-52
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• 2008

In this paper, we propose a new selective subspace projection method in order to recognize the occlusive face image effectively. The conventional subspace projection method is project to basis image using a full image of face. The face recognition rate has reduced because the face characteristic is easy to be distorted by occlusion. To overcome this problem, the proposed method first decide to occlusion. If it hasn't an occlusion, we get the feature vectors with total basis projection using the conventional subspace projection method. If it has an occlusion, we get one with partial basis projection. We get better recognition rate than conventional PCA and NMF using AR face database with occlusive face images.

• Journal of the Korean Society of Food Culture
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• v.25 no.6
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• pp.661-670
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• 2010

Although many studies have suggested that introducing the distance learning method, including Web-based learning, to a practice class is effective, studies applying the distance learning method to subjects who are practicing cooking are rare. The purpose of this study was to determine the perception of the distance learning method, the degree of computer use, and the use of distance learning by college students with cuisine-related majors to practice cooking. The results showed that most students used the distance learning method, and that the method was positively perceived, as it was a great aid in learning. Most of the cooking information was obtained through the internet, and the most effective learning media for practicing cooking was "e-learning" using a computer. The most effective learning method for those who were practicing cooking was a "face-to-face learning method", because face-to-face type of teaching and learning was most universally recognized. Most of the students surveyed responded that using the distance learning method was a positive experience, indicating that cyber lectures could be applied at more universities for subjects practicing cooking.

• Journal of Multimedia Information System
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• v.2 no.1
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• pp.171-178
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• 2015

This article describes 3 dimensional (3D) face recognition system using histogram of oriented gradients (HOG) based on face curvature. The surface curvatures in the face contain the most important personal feature information. In this paper, 3D face images are recognized by the face components: cheek, eyes, mouth, and nose. For the proposed approach, the first step uses the face curvatures which present the facial features for 3D face images, after normalization using the singular value decomposition (SVD). Fisherface method is then applied to each component curvature face. The reason for adapting the Fisherface method maintains the surface attribute for the face curvature, even though it can generate reduced image dimension. And histogram of oriented gradients (HOG) descriptor is one of the state-of-art methods which have been shown to significantly outperform the existing feature set for several objects detection and recognition. In the last step, the linear discriminant analysis is explained for each component. The experimental results showed that the proposed approach leads to higher detection accuracy rate than other methods.

• Geomechanics and Engineering
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• v.30 no.4
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• pp.363-372
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• 2022

One of the most frequent issues in tunnel excavation is the collapse of rock blocks and the dropping of rock fragments from the tunnel face. The tunnel face can be reinforced using a number of techniques. One of the most popular and affordable solutions is the use of face longitudinal dowels, which has benefits including high strength, flexibility, and ease of cutting. In order to examine the reinforced face, this work shows the longitudinal deformation profile and ground response curve for a tunnel face. This approach is based on assumptions made during the analysis phase of problem solving. By knowing the tunnel face response and dowel behavior, the interaction of two elements can be solved. The rock element equation derived from the rock bolt method is combined with the dowel differential equation to solve the reinforced ground response curve (GRC). With a straightforward and accurate analytical equation, the new differential equation produces the reinforced displacement of the tunnel face at each stage of excavation. With simple equations and a less involved computational process, this approach offers quick and accurate solutions. The FLAC3D simulation has been compared with the suggested analytical approach. A logical error is apparent from the discrepancies between the two solutions. Each component of the equation's effect has also been described.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.45-53
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• 2022

The avionics industry has recently adopted an open architecture to increase software portability and reduce the development schedule and cost associated with changing hardware equipment. This paper presents a data modeling method compliant with FACE, a widely used open avionics architecture. A FACE data model is designed and implemented to output data from VOR/ILS avionics equipment. A FACE Conformance Test Suite (CTS) program is utilised to verify that the data model meets FACE standards. The proposed data modeling method is expected to improve the development schedule and cost associated with modifying communication methods and ICDs (Interface Control Documents).

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.529-532
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• 2003

In this paper, we describe new method to detect face in real-time. We use color information, edge information, and binary information to detect candidate regions of eyes from input image, and then extract face region using the detected eye pall. We verify both eye candidate regions and face region using Support Vector Machines(SVM). It is possible to perform fast and reliable face detection because we can protect false detection through these verification processes. From the experimental results, we confirmed the proposed algorithm shows very excellent face detection performance.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.1-49
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• 2001

The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.54-60
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• 2010

The local appearance-based method is one of the face recognition methods that divides face image into small areas and extracts features from each area of face image using statistical analysis. It collects classification results of each area and decides identity of a face image using a voting scheme by integrating classification results of each area of a face image. The conventional local appearance-based method divides face images into small pieces and uses all the pieces in recognition process. In this paper, we propose a local appearance-based method that makes use of only the relatively important facial components. The proposed method detects the facial components such as eyes, nose and mouth that differs much from person to person. In doing so, the proposed method detects exact locations of facial components using support vector machines (SVM). Based on the detected facial components, a number of small images that contain the facial parts are constructed. Then it extracts features from each facial component image using principal components analysis (PCA). We compared the performance of the proposed method to those of the conventional methods. The results show that the proposed method outperforms the conventional local appearance-based method while preserving the advantages of the conventional local appearance-based method.

• Journal of Korean Dental Hygiene Science
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• v.4 no.2
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• pp.53-65
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• 2021

Background: To survey and analyze awareness and recognition during a non-face-to-face lecture, and satisfaction with among dental technology students. Methods: Total 179 undergraduates were surveyed from the Department of Dental Technology. Frequency analysis, cross analysis, independent sample t-test, correlation analysis, and multiple regression analysis were used for analyzing statistics. Results: Overall satisfaction with the non-face-to-face lecture was the highest (p=.037) while watching a recorded lecture in the theory curriculum subject. In the case of practical subjects, satisfaction with face-to-face lectures appeared to be higher (p=.039) compared to non-face-to-face lectures. Factors influencing the recognition of non-face-to-face lecture quality included awareness of a place to conduct a class and of face-to-face delivered lecture quality, satisfaction with face-to-face lecture, and satisfaction with non-face-to-face lecture. Factors affecting satisfaction with a non-face-to-face lecture included a place to conduct a class, the most effective theory non-face-to-face class method, the method of having been experienced the most among non-face-to-face lecture methods, and the recognition of non-face-to-face lecture quality. Conclusions: Future educational environment should include combined face-to-face and non-face-to-face lectures. An efficient educational indicator will be needed to evaluate learners' assessments and opinions about online classes, followed by its application to teaching methods.