• KSCE Journal of Civil and Environmental Engineering Research
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• 제26권5C호
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• pp.351-358
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• 2006

The purpose of this study is to recommend the simulation method and procedure of behaviors of CFRD(Concrete Faced Rockfill Dam) concrete face slab with impoundment by centrifuge tests, to examine the effects of the flexural rigidity of the concrete face slab on the face slab deformation from the centrifuge tests, and to evaluate the effects of the stiffness of face supporting zone on the displacement and moment of face slab by numerical analysis which is verified by the centrifuge tests. In this study, the centrifuge tests on the two model dams with the concrete face slab of different flexural rigidity were carried out. Also, the centrifuge tests were simulated by numerical analysis of which input material properties were obtained by the triaxial tests on the model materials. The validity of numerical analysis was evaluated by comparison between the results of centrifuge tests and numerical simulation. The deformation pattern of the concrete face slab was examined with the various stiffness of the face supporting zone by numerical analysis. From the results of centrifuge tests, the effects of face slab thickness on the deformation of face slab were negligible. From the results of centrifuge tests and numerical analysis, it was found that the amplitude of the maximum displacement of face slab and the position where the maximum displacement was mobilized with impoundment were affected by the stiffness of face supporting zone rather than the flexural rigidity of concrete face slab.

• Journal of Korea Multimedia Society
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• 제18권5호
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• pp.610-619
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• 2015

*In this paper, we propose a real-time face tracking system using an adaptive face detector and a tracking algorithm. An image is divided into the regions of background and face candidate by a real-time updated skin color identifying system in order to accurately detect facial features. The facial characteristics are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted by Principal Component Analysis (PCA), and the interpreted principal components are processed by Support Vector Machine (SVM) that classifies into facial and non-facial areas. The movement of the face is traced by Kalman filter and Mean shift, which use the static information of the detected faces and the differences between previous and current frames. The proposed system identifies the initial skin color and updates it through a real-time color detecting system. A similar background color can be removed by updating the skin color. Also, the performance increases up to 20% when the background color is reduced in comparison to extracting features from the entire region. The increased detection rate and speed are acquired by the usage of Kalman filter and Mean shift.

• Journal of Korea Society of Digital Industry and Information Management
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• 제11권3호
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• Journal of Korea Multimedia Society
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• 제6권7호
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• pp.1139-1148
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• 2003

Biometric system has been studied as an optimal solution for preventing or reducing the peculation or loss of ID. Nowadays, face recognition has been spot-lighted as a future biometric system because it is not forced to contact the part of human body with the specific input area of the system. However, there is some limitations to get the constant facial features because the size of face area is varied by the capturing distance or tilt of the face. In this paper, we can extract constant facial features within the predefined threshold using the simple geometric processing such as image scaling, transformation, and rotation for frontal face images. This face recognition system identifies faces with 92% of accuracy for the 400 images of 40 different people.

• Journal of the Korea Computer Graphics Society
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• 제22권2호
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• pp.20-26
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• 2016

This paper proposes an automatic hexahedral mesh generation method, in which internal medial surfaces are established to partition a region using the face-offsetting method. In order to test the usability of the suggested method, aspect ratios and Jacobians of the generated mesh for two models are evaluated and compared with ones from existing methods. It is verified that the proposed medial surface generation and partitioning scheme based on the face-offsetting method can be effectively used in the automatic hexahedral mesh generation procedure.

• Journal of KIISE:Computing Practices and Letters
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• 제16권8호
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• pp.883-887
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• 2010

3D face tracking is one of essential techniques in computer vision such as surveillance, HCI (Human-Computer Interface), Entertainment and etc. However, 3D face tracking demands high computational cost. It is a serious obstacle to applying 3D face tracking to mobile devices which usually have low computing capacity. In this paper, to reduce computational cost of 3D tracking and extend 3D face tracking to mobile devices, an efficient particle filtering method using MLESAC(Maximum Likelihood Estimation SAmple Consensus) motion estimation is proposed. Finally, its speed and performance are evaluated experimentally.

• Journal of Information Processing Systems
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• 제9권1호
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• pp.141-156
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• 2013

In this paper we propose a method to detect human faces in color images. Many existing systems use a window-based classifier that scans the entire image for the presence of the human face and such systems suffers from scale variation, pose variation, illumination changes, etc. Here, we propose a lighting insensitive face detection method based upon the edge and skin tone information of the input color image. First, image enhancement is performed, especially if the image is acquired from an unconstrained illumination condition. Next, skin segmentation in YCbCr and RGB space is conducted. The result of skin segmentation is refined using the skin tone percentage index method. The edges of the input image are combined with the skin tone image to separate all non-face regions from candidate faces. Candidate verification using primitive shape features of the face is applied to decide which of the candidate regions corresponds to a face. The advantage of the proposed method is that it can detect faces that are of different sizes, in different poses, and that are making different expressions under unconstrained illumination conditions.

• Journal of the Korea Computer Industry Society
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• 제3권12호
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• pp.1765-1774
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• 2002

A face recognition is currently the field which many research have been processed actively. But many problems must be solved the previous problem. First, We must recognize the face of the object taking a location various lighting change and change of the camera into account. In this paper, we proposed that new method to fund feature within fast and correct computation time after scanning PC camera and ID card picture. It converted RGB color space to YUV. A face skin color extracts which equalize a histogram of Y ingredient without the luminance. After, the method use V' ingredient which transformes V ingredient of YUV and then find the face feature. The reult of the experiment shows getting correct input face image from ID Card picture and PC camera.

• Maxillofacial Plastic and Reconstructive Surgery
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• 제23권1호
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• pp.59-69
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• 2001

Purpose : The purpose of the present study was to evaluate postoperative stability and soft-tissue osseous relations of the long face syndrome patients. Methods : Twenty-five patients who had undergone bimaxillary surgery to correct long face syndrome at the Pusan National University Hospital were evaluated. The lateral cephalograms of preoperative, 1 week postoperative and at least 1 year postoperative were examined. Results : 1. The facial height of the long face syndrome patients were longer than normal Korean adults. 2. The most common malocclusion type of the long face syndrome patients in Korea was class III. 3. Horizontal postoperative skeletal relapses were $-0.64{\sim}0.80mm$ in the maxilla, and $-0.56{\sim}0.48mm$ in the mandible. 4. Vertical postoperative skeletal relapses were $0.20{\sim}0.56mm$ in the maxilla, and $-0.80{\sim}0.20mm$ in the mandible. 5. Postoperative soft tissue changes in long face syndrome patients were correlated with postoperative skeletal changes. So prediction schemes for postoperative soft-tissue changes were obtainable. Conclusion : It is hard to predict the exact direction and quantity of the postoperative skeletal relapse in long face syndrome patient's orthognathic surgery because of large standard deviation. But soft tissue change is predictable via prediction scheme.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.246-252
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• 2020

Facial recognition is a biometric technology that is used in various fields such as user authentication and identification of human characteristics. Face recognition applications are practically used in various fields, but very few applications have been developed to improve the factory work environment. We implemented applications that uses face recognition to identify a specific employee in a factory .work environment and provide customized information for each employee. Factory workers need documents describing the work in order to do their assigned work. Factory managers can use our application to register documents needed for each worker, and workers can view the documents assigned to them. Each worker is identified using face recognition, and by tracking the worker's face during work, it is possible to know that the worker is in the workplace. In addition, as a mobile app for workers is provided, workers can view the contents using a tablet, and we have defined a simple communication protocol to exchange information between our applications. We demonstrated the applications in a factory work environment and found several improvements were required for practical use. We expect these results can be used to improve factory work environments.