• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.186-196
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• 2010

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.59-68
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• 2005

This paper proposes a face recognition under varying poses using local area obtained by side-view pose normalization. General normalization methods for face recognition under varying pose have a problem with the information about invisible area of face. Generally this problem is solved by compensation, but there are many cases where the image is distorted or features lost due to compensation .To solve this problem we normalize the face pose in side-view to reduce distortion that happens mainly in areas that have large depth variation. We only use undistorted area, removing the area that has been distorted by normalization. We consider two cases of yaw pose variation and pitch pose variation, and by experiments, we confirm the improvement of recognition performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.748-753
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• 2012

In this paper, Face recognition algorithm is designed based on optimized pRBFNNs pattern classifier using three-dimensional scanner. Generally two-dimensional image-based face recognition system enables us to extract the facial features using gray-level of images. The environmental variation parameters such as natural sunlight, artificial light and face pose lead to the deterioration of the performance of the system. In this paper, the proposed face recognition algorithm is designed by using three-dimensional scanner to overcome the drawback of two-dimensional face recognition system. First face shape is scanned using three-dimensional scanner and then the pose of scanned face is converted to front image through pose compensation process. Secondly, data with face depth is extracted using point signature method. Finally, the recognition performance is confirmed by using the optimized pRBFNNs for solving high-dimensional pattern recognition problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.539-544
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• 2013

In this paper, we was designed three-dimensional face recognition algorithm using polynomial based RBFNNs and proposed method to calculate the recognition performance. In case of two-dimensional face recognition, the recognition performance is reduced by the external environment like facial pose and lighting. In order to compensate for these shortcomings, we perform face recognition by obtaining three-dimensional images. obtain face image using three-dimension scanner before the face recognition and obtain the front facial form using pose-compensation. And the depth value of the face is extracting using Point Signature method. The extracted data as high-dimensional data may cause problems in accompany the training and recognition. so use dimension reduction data using PCA algorithm. accompany parameter optimization using optimization algorithm for effective training. Each recognition performance confirm using PSO, DE, GA algorithm.

• The Journal of Fisheries Business Administration
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• v.25 no.1
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• pp.1-17
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• 1994

Coastal economic activities usually generate externalities to other economic activities. The conflicts between coastal economic activities, especially land fillings and reclamations, and fisheries in coastal waters pose a typical one, which sometimes causes some social conflicts. In this regard, as the contents and requirements for rules and regulations on fisheries compensation may have important implications for solving such problems, important is to review rationales fur the formulas in calculating fisheries compensation. The purpose of this paper is to review the formulas for fisheries compensation from the economic view points, to highlight some problems and to suggest more appropriate formulas. It is found that the current formulas of fisheries compensation are not properly based on economic concepts and valuation techniques. Main problems are related, as followings, to the coefficient(0.8) employed in the formula, to fishermen's own wages and to current values of invested assets such as fishing boats and nets, etc.. First, it is not clear what the coefficient(0, 8) means. In Japan's case, the coefficient was assumed to reflect the opportunity cost of fishermen's own wages, but it was disappeared from the formula after the self-wage came to be included in totaling fishing cost. As our new formula will include the self-wage in fishing cost, the coefficient(0.8) should be excluded. Second, according to our formula, the current value of invested assets is added to total operating compensation, which will overestimate total compensation. Therefore, it is suggested that total present value of the assets to be invested during the business life should be deducted from total operating compensation. Third, as the self-wage will be included in total cost, opportunity cost for finding new jobs should be newly added to the formula. Finally, this paper also conducted a comparative case study considering above-mentioned factors. The case study showed that the current formulas overestimated total fisheries compensation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.155-164
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user and is able to doface recognition, which is vital for many surveillance-based systems. The advantage of face recognition compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to the decreasing in dimension from image acquisition step and various changes associated with face pose and background. There are many factors that deteriorate performance of face recognition such as thedistance from camera to the face, changes in lighting, pose change, and change of facial expression. In this paper, we implement a new sliding active camera system to prevent various pose variation that influence face recognition performance andacquired frontal face images using PCA and HMM method to improve the face recognition. This proposed face recognition algorithm can be used for intelligent surveillance system and mobile robot system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.797-803
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• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.900-911
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• 2015

In this paper, 3D face recognition model is designed by using Polynomial based RBFNN(Radial Basis Function Neural Network) and PNN(Polynomial Neural Network). Also recognition rate is performed by this model. In existing 2D face recognition model, the degradation of recognition rate may occur in external environments such as face features using a brightness of the video. So 3D face recognition is performed by using 3D scanner for improving disadvantage of 2D face recognition. In the preprocessing part, obtained 3D face images for the variation of each pose are changed as front image by using pose compensation. The depth data of face image shape is extracted by using Multiple point signature. And whole area of face depth information is obtained by using the tip of a nose as a reference point. Parameter optimization is carried out with the aid of both ABC(Artificial Bee Colony) and PSO(Particle Swarm Optimization) for effective training and recognition. Experimental data for face recognition is built up by the face images of students and researchers in IC&CI Lab of Suwon University. By using the images of 3D face extracted in IC&CI Lab. the performance of 3D face recognition is evaluated and compared according to two types of models as well as point signature method based on two kinds of depth data information.

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.367-418
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• 2018

Just as safety is the most important thing in aviation, safety is the most important in the operation of unmanned aircraft (RPA), and safety operation is the most important in the legal responsibility of the operator of the unmanned aircraft. In this thesis, the legal responsibility of the operator of the unmanned aircraft, focusing on the responsibility of the operator of the unmanned aircraft, was discussed in depth with the issue of insurance, which compensates for damages in the event of an accident First of all, the legal responsibility of the operator of the unmanned aircraft was reviewed for the most basic : definition, scope and qualification of the operator of the unmanned aircraft, and the liability of the operator of the Convention On International Civil Aviation, the ICAO Annex, the RPAS Manual, the Rome Convention, other major international treaties and Domestic law such as the Aviation Safety Act. The ICAO requires that unmanned aircraft be operated in such a manner as to minimize hazards to persons, property or other aircraft as a major principle of the operation of unmanned aircraft, which is ultimately equivalent to manned aircraft Considering that most accidents involving unmanned aircrafts fall to the ground, causing damage to third parties' lives or property, this thesis focused on the responsibility of operators under the international treaty, and the responsibility of third parties for air transport by Domestic Commercial Act, as well as the liability for compensation. In relation to the Rome Convention, the Rome Convention 1952 detailed the responsibilities of the operator. Although it has yet to come into effect regarding liability, some EU countries are following the limit of responsibility under the Rome Convention 2009. Korea has yet to sign any Rome Convention, but Commercial Act Part VI Carriage by Air is modeled on the Rome Convention 1978 in terms of compensation. This thesis also looked at security-related responsibilities and the responsibility for privacy infringement. which are most problematic due to the legal responsibilities of operating unmanned aircraft. Concerning insurance, this thesis looked at the trends of mandatory aviation insurance coverage around the world and the corresponding regulatory status of major countries to see the applicability of unmanned aircraft. It also looked at the current clauses of the Domestic Aviation Business Act that make insurance mandatory, and the ultra-light flight equipment insurance policy and problems. In sum, the operator of an unmanned aircraft will be legally responsible for operating the unmanned aircraft safely so that it does not pose a risk to people, property or other aircraft, and there will be adequate compensation in the event of an accident, and legal systems such as insurance systems should be prepared to do so.