• Tunnel and Underground Space
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• v.5 no.2
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• pp.95-103
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• 1995

In this paper the stress redistribution around tunnel face was analyzed by using a three-dimensional finite element model. The effects of in-situ stress levels, excavation sequences, stiffness difference between the hard ground and the weak zone on the stress redistributions were considered. Displacement and stress changes at tunnel crown, side wall, and invert were investigated throughout the sequential excavation. To show ground response, percentage of the displacement and stress variations are used as a function of normalized distance that is between the face and monitoring section. Preceding displacements and stress variations were presented to be adopted in the two-dimensional tunnel analysis.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.113-121
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• 2005

Face detection in real-time video constitutes one of the major trend in face recognition. In this paper, we propose a face detection algorithm using the skin color and Haar-like feature in real-time video. The proposed algorithm is followed by three sequences; First, moving objects are detected by difference-method in YCbCr coordinates, and then by using Haar-like features, face candidate regions of the moving objects is selected. Finally we extract the most possible face candidates by comparing the pixel values of face candidates with the skin color. In order to prevent a mistake. we use similar features or skin color to detect a face by selecting a adaptive ROI and improve the processing speed in real-time video. The computer simulation shows the validity of the proposed method that the processing speed is improved by 30% than previous works and the detection success rate is 96.8%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.16-24
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• 2005

In this paper, we proposed a face tracking algorithm for a viewpoint adaptive multi-view synthesis system. The original scene captured by a depth camera contains a texture image and 8 bit gray-scale depth map. From this original image, multi-view images can be synthesized which correspond to viewer's position by using geometrical transformation such as a rotation and a translation. The proposed face tracking technique gives a motion parallax cue by different viewpoints and view angles. In the proposed algorithm, tracking of viewer's dominant face initially established from camera by using statistical characteristics of face colors and deformable templates is done. As a result, we can provide motion parallax cue by detecting viewer's dominant face area and tracking it even under a heterogeneous background and can successfully display the synthesized sequences.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1074-1081
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• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• BMB Reports
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• v.38 no.5
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• pp.550-554
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• 2005

YKR049C is a mitochondrial protein in Saccharomyces cerevisiae that is conserved among yeast species, including Candida albicans. However, no biological function for YKR049C has been ascribed based on its primary sequence information. In the present study, NMR spectroscopy was used to determine the putative biological function of YKR049C based on its solution structure. YKR049C shows a well-defined thioredoxin fold with a unique insertion of helices between two $\beta$-strands. The central $\beta$-sheet divides the protein into two parts; a unique face and a conserved face. The 'unique face' is located between ${\beta}2$ and ${\beta}3$. Interestingly, the sequences most conserved among YKR049C families are found on this 'unique face', which incorporates L109 to E114. The side chains of these conserved residues interact with residues on the helical region with a stretch of hydrophobic surface. A putative active site composed by two short helices and a single Cys97 was also well observed. Our findings suggest that YKR049C is a redox protein with a thioredoxin fold containing a single active cysteine.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.385-394
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• 2009

Face tracking and recognition are difficult problems because the face is a non-rigid object. The main reasons for the failure to track and recognize the faces are the changes of a face pose and environmental illumination. To solve these problems, we propose a nonlinear manifold framework for the face pose and the face illumination normalization processing. Specifically, to track and recognize a face on the video that has various pose variations, we approximate a face pose density to single Gaussian density by PCA(Principle Component Analysis) using images sampled from training video sequences and then construct the GMM(Gaussian Mixture Model) for each person. To solve the illumination problem for the face tracking and recognition, we decompose the face images into the reflectance and the illuminance using the SSR(Single Scale Retinex) model. To obtain the normalized reflectance, the reflectance is rescaled by histogram equalization on the defined range. We newly approximate the illuminance by the trained manifold since the illuminance has almost variations by illumination. By combining these two features into our manifold framework, we derived the efficient face tracking and recognition results on indoor and outdoor video. To improve the video based tracking results, we update the weights of each face pose density at each frame by the tracking result at the previous frame using EM algorithm. Our experimental results show that our method is more efficient than other methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.25-33
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• 2010

In this paper, we propose a simple and efficient algorithm for head pose estimation using a single camera. First, four subimages are obtained from the camera image for face feature extraction. These subimages are used as feature templates. The templates are then tracked by Kalman filtering, and camera projective matrix is computed by the projective mapping between the templates and their coordinate in the 3D coordinate system. And the user's face pose is estimated from the projective mapping between the user's face and image plane. The accuracy and the robustness of our technique is verified on the experimental results of several real video sequences.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3329-3334
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• 2016

Cancer is thought to be a direct result of transcriptional misregulation. Broad analysis of transcriptional regulatory elements in healthy and cancer cells is needed to understand cancer development. Nucleases regulatory domains are recruited to bind and manipulate a specific genomic locus with high efficacy and specificity. TALENs (transcription activator-like effector nuclease) fused to endonuclease FokI have been used widely to target specific sequences to edit several genes in healthy and cancer cells. This approach is promising to target specific cancer genes and for this purpose it is needed to pack such TALENs into viral vectors. There are some considerations which control the success of this approach, targeting appropriate sequences with efficient construction of TALENs being crucial factors. We face some obstacles in construction of TALENs; in this study we made a modification to the method of Cermk et al 2011 and added one step to make it easier and increase the availability of constructs.