• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.87-97
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• 2020

In this paper, we propose a novel neural relighting that infers a relighted rendering image based on the user-guided specular highlight map. The proposed network utilizes a pre-trained neural renderer as a backbone network learned from the rendered image of a 3D scene with various lighting conditions. We jointly optimize a 3D light position and its associated relighted image by back-propagation, so that the difference between the base image and the relighted image is similar to the user-guided specular highlight map. The proposed method has the advantage of being able to explicitly infer the 3D lighting position, while providing the artists' preferred 2D screen-space interface. The performance of the proposed network was measured under the conditions that can establish ground truths, and the average error rate of light position estimations is 0.11, with the normalized 3D scene size.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.6
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• pp.55-62
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• 2006

For the fault diagnosis of three-phase induction motors, we construct a experimental unit and then develop a diagnosis algorithm based on pattern recognition. The experimental unit consists of machinery module for induction motor drive and data acquisition module to obtain the fault signal. As the first step for diagnosis procedure, preprocessing is performed to make the acquired current simplified and normalized. To simplify the data, three-phase current is transformed into the magnitude of Concordia vector. As the next step, feature extraction is performed by kernel principal component analysis(KPCA) and linear discriminant analysis(LDA). Finally, we used the classifier based on radial basis function(RBF) network. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2002.11a
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• pp.133-138
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• 2002

As Information society has expanded in large scale. In order to improve the reliability and Qos(Qualify of service), domestic IDC(Internet Data Center) has adopted or will adopt the SLAs(Service Level Agreements). The power quality of internet hosting server unit, power system and UPS is very important for better internet service. Therefore, the higher reliability of power system is imperative for satisfying SLAs. This paper presents the status measurement of domestic IDCs harmonics and illustrates the reduction effect of harmonics through the multi-phase.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.109-118
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• 2002

As Information society has expanded in large scale. In order to improve the reliability and Qos(Quality of service), domestic IDC(Internet Data Center) has adopted or will adopt the SLAs(Service Level Agreements). The power quality of internet hosting server unit, power system and UPS is very important for better internet service. Therefore, the higher reliability or power system is imperative for satisfying SLAs. This paper presents the status measurement of domestic IDCs harmonics and illustrates the reduction effect of harmonics through the multi-phase.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.19-32
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• 2007

This paper present a new face recognition method based on LVQ neural net to construct a real time face recognition system. The previous researches which used PCA, LDA combined neural net usually need much time in training neural net. The supervised LVQ neural net needs much less time in training and can maximize the separability between the classes. In this paper, the proposed method transforms the input face image by PCA and LDA sequentially into low-dimension feature vectors and recognizes the face through LVQ neural net. In order to make the system robust to external light variation, light compensation is performed on the detected face by max-min normalization method as preprocessing. PCA and LDA transformations are applied to the normalized face image to produce low-level feature vectors of the image. In order to determine the initial centers of LVQ and speed up the convergency of the LVQ neural net, the K-Means clustering algorithm is adopted. Subsequently, the class representative vectors can be produced by LVQ2 training using initial center vectors. The face recognition is achieved by using the euclidean distance measure between the center vector of classes and the feature vector of input image. From the experiments, we can prove that the proposed method is more effective in the recognition ratio for the cases of still images from ORL database and sequential images rather than using conventional PCA of a hybrid method with PCA and LDA.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.3-12
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• 2020

The purpose of this work is to suggest the optimal color temperature, which induces a sense of comfort for autonomous vehicle users through the analysis of biosignal using electroencephalography (EEG) and photoplethysmography (PPG). To achieve this purpose, we applied lighting with a color temperature of 3000 K, 4000 K, 5000 K, and 6000 K to the autonomous driving environment. We experimented in a laboratory equipped with a graphic driving simulator. The experimental procedure is as follows: 1) stabilization (5 min). 2) Uchida-Kraepelin test (3 min). 3) Automatic driving + lighting (3 min). This procedure was repeated four times under different color temperatures. We performed frequency analysis on a collected time-series data and calculated the power value for each frequency band through power spectrum analysis. In the case of EEG, we analyzed α- and β-waves, which are indicators of stability and arousal, respectively. In the case of PPG, we analyzed the sympathetic nervous system activity. To reduce deviations between the subjects, we normalized the data before analysis. The result of the first analysis revealed that α-wave increased only at 5000 K, while the β-wave increased at almost all color temperatures. In addition, in the case of PPG, sympathetic nervous system activity (SNSA) increased under driving conditions. The result of the second analysis revealed that the difference between β-wave and SNSA is insignificant. In conclusion, the increase in α-waves showed that EEG was most stable at 5000 K. The results of this study can be applied to the upcoming autonomous driving era to induce high driver satisfaction. Furthermore, this approach could eventually lead to the acceptance of autonomous vehicles by suggesting a positive effect of autonomous driving.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.109-117
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• 2000

A full bridge type double resonant high frequency resonant inverter to give VVVF function in the inverter used as power source of induction heating at high frequency is presented in this paper. This proposed inverter can reduce distribution of the switching current because of using the current of serial resonant circuit to the input current of the parallel one and this paper also realize the output control of independence irrespective of the switching frequency using Phase-shift. The analysis of the proposed circuit is generally described by using the normalized parameters. Also, the principle of basic operating and the its characteristics are estimated by the parameters, such as switching frequency, the variation of phase angle ($\phi$) of Phase-shift.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.4
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• pp.65-72
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• 2000

This paper proposes a Push type High Frequency DC-DC Converter using Zero Voltage Switching to reduce turn on and off loss at the switching instants. This paper has a advantage which is able to operating safely in load short, because DC reactor is connected with resonance reactor in order to supply a fixed safely in load short, because DC reactor is connected with resonance reactor in order to supply a fixed current with low ripple from DC power supply. The capacitor $(C_1, C_2)$ connected in switch are a common using as resonance capacitor and ZVS capacitor. The analysis of the proposed high frequency resonance DC-DC converter is generally described by using normallized parameter, and we has evaluated characteristic values which is needed to design a circuit. We conform a rightfulness of theoritical analysis by comparing a theoretical values and experimental values obtained from experiment using MOSFET as switching devices.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.1
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• pp.90-97
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• 2001

A high frequency resonant inverter consisting of iliree unit Half-Bridge serial resommt inverter used as power source of induction heatmg at high frequency is presented in this paper. As a output [Dwer control strategy, sequencial time-sharing gate contml methcd is applied. This methcd is TDM(Time Division Multiplexing), which is broadly used with digital and analog signals transmission in communication system 1be analysis of the proposed circuit is generally described by using the normalized pararmenters. Also, the principle of basic operating and the its characteristics are estimated by the parameters such as switching frequency, load resistance. Also, according to the calculated characteristics value, a method of the circuit design and operating characteristics of the inverter is proposed. This paper proves the validity of theoretical analysis through the Pspice. This proposed inverter show that it can be practically used in future as power source system for induction heating application, DC-DC converter etc. r etc.