• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.153-160
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• 2011

Recently, the use of security surveillance system including CCTV is increasing due to the increase of terrors and crimes. At the same time, interest of face recognition at a distance using surveillance cameras has been increasing. Accordingly, we analyzed the performance of face recognition according to distance using PCA-based face recognition and interpolation. In this paper, we used Nearest, Bilinear, Bicubic, Lanczos3 interpolations to interpolate face image. As a result, we confirmed that existing interpolation have an few effect on performance of PCA-based face recognition and performance of PCA-based face recognition is improved by including face image according to distance in traning data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.984-994
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• 2010

Pose variation is a critical problem in face recognition. Three-dimensional(3D) face recognition techniques have been proposed, as 3D data contains depth information that may allow problems of pose variation to be handled more effectively than with 2D face recognition methods. This paper proposes a pose-normalized 3D face modeling method that translates and rotates any pose angle to a frontal pose using a plane fitting method by Singular Value Decomposition(SVD). First, we reconstruct 3D face data with stereo vision method. Second, nose peak point is estimated by depth information and then the angle of pose is estimated by a facial plane fitting algorithm using four facial features. Next, using the estimated pose angle, the 3D face is translated and rotated to a frontal pose. To demonstrate the effectiveness of the proposed method, we designed 2D and 3D face recognition experiments. The experimental results show that the performance of the normalized 3D face recognition method is superior to that of an un-normalized 3D face recognition method for overcoming the problems of pose variation.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.487-495
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• 2010

It has been required to develop an accurate and reliable evaluation method for the performance of biometric systems as their use is getting popular. Among a number of biometric systems, face recognition is one of the most widely used techniques and this leads to develop a stable evaluation method for face recognition systems in order to standardize the performance of face recognition systems. However, it is considered as a difficult task to evaluation such systems due to a large number of factors that affect their performance. Thus, it may be infeasible to take into account all the environmental factors that are related to the performance of face recognition systems and this naturally suggests an evaluation method for the overall performance based on scenarios. In this paper, we have analyzed environmental factors that are related to the performance of general face recognition systems and proposed their evaluation method taking into account those factors. We have proposed an evaluation method based on scenario that considers the combination of individual environment factors instead of evaluating the performance of face recognition systems regarding each factor. Indeed, we have presented examples on the evaluation of face recognition systems based on scenario that takes into account overall environmental factors.

• The KSFM Journal of Fluid Machinery
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• v.10 no.1 s.40
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• pp.20-25
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• 2007

A mechanical face seal has been tested in Korea Aerospace Research Institute for turbopump applications. In this paper the acceptance test results of the mechanical face seal are described. By means of simulating a practical operating environment, the performance against leakage of mechanical face seal is monitored. In addition the carbon wear is measured to estimate the life of a mechanical face seal. The test results show the acceptable leakage performance and resonable wear tendency as well. Lastly the repeated test had been carried out to guarantee the endurance performance of mechanical face seal based on the turbopump life.

• Tribology and Lubricants
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• v.32 no.5
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• pp.154-159
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• 2016

This paper presents an experimental study of the leakage performance and endurance performance of a mechanical face seal in the 7-ton-class turbopump of the Korea Space Launch Vehicle 2 third-stage engine. We install a mechanical face seal between the fuel pump and turbine to prevent the mixing of the fuel and turbine gas. We design and manufacture a prototype mechanical face seal, which has two parts, namely, a bellows seal assembly and mating ring. We set up a test facility to measure the leakage and endurance of the mechanical face seal. For the similarity tests, we use water under real operating conditions such as high rotational speed, high temperature, and high pressure. Through investigation of the leakage and carbon wear rate, it is possible to evaluate the performance of the mechanical face seal. The results of the leakage and endurance performance test demonstrate the absence of any leakage from the prototype mechanical face seal after a trial run and clarify that the acceptable wear rate fully satisfies the turbopump requirements. Finally, we install a qualified mechanical face seal in a 7-ton-class turbopump and perform a validation test in the turbopump real-propellant test facility in the Korea Aerospace Research Institute. The test results confirm that the mechanical face seal works well under real operating conditions.

• Steel and Composite Structures
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• v.19 no.2
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• pp.485-501
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• 2015

Channels are implemented in composite beams as shear connectors in two arrangements, face to face and back to back. No relevant explanation is found in the design codes to clarify the preference of the mentioned arrangements. Besides, the designers do not have a common opinion on this subject; i.e., some recommend the face to face and others, back to back status. In this research, channel shear connectors in composite beams are studied analytically for both arrangements using ABAQUS software. For this purpose, they have been modeled in simply supported beams in the arrangements of face to face and back to back; their effects on the crack initiation load of concrete slabs were monitored. The stiffness values of composite beams were also compared in the two arrangements using force-displacement curve; the results are relatively the same in both cases. Furthermore, the effects of compressive strength of concrete, channel size, length and spacing of channels as well as steel type of channels on the performance of composite beams have been investigated. According to the results obtained in this research, the face to face status shows better performance in comparison with that of back to back, considering the load of concrete fracturing.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.43-53
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• 2018

As face recognition (FR) has been well studied over the past decades, FR technology has been applied to many real-world applications such as surveillance and biometric systems. However, in the real-world scenarios, FR performances have been known to be significantly degraded owing to variations in face images, such as the pose, illumination, and low-resolution. Recently, visual intelligence technology has been rapidly growing owing to advances in deep learning, which has also improved the FR performance. Furthermore, the FR performance based on deep learning has been reported to surpass the performance level of human perception. In this article, we discuss deep-learning based high-performance FR technologies in terms of representative deep-learning based FR architectures and recent FR algorithms robust to face image variations (i.e., pose-robust FR, illumination-robust FR, and video FR). In addition, we investigate big face image datasets widely adopted for performance evaluations of the most recent deep-learning based FR algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.777-786
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• 2008

Human face avatar is important information in nowadays, such as describing real people in virtual world. In this paper, we have presented a face avatar creation and warping algorithm by using face feature analysis method, in order to detect face feature, we utilized local mean method based on facial feature appearance and face geometric information. Then detect facial candidates by using it's character in $YC_bC_r$ color space. Meanwhile, we also defined the rules which are based on face geometric information to limit searching range. For analyzing face feature, we used face feature points to describe their feature, and analyzed geometry relationship of these feature points to create the face avatar. Then we have carried out simulation on PC and embed mobile device such as PDA and mobile phone to evaluate efficiency of the proposed algorithm. From the simulation results, we can confirm that our proposed algorithm will have an outstanding performance and it's execution speed can also be acceptable.