• Journal of Information Processing Systems
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• v.11 no.4
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• pp.643-654
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• 2015

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.781-784
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• 2014

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we use Affine SIFT to detect affine invariant local descriptors for face recognition under large viewpoint change. Affine SIFT is an extension of SIFT algorithm. SIFT algorithm is scale and rotation invariant, which is powerful for small viewpoint changes in face recognition, but it fails when large viewpoint change exists. In our scheme, Affine SIFT is used for both gallery face and probe face, which generates a series of different viewpoints using affine transformation. Therefore, Affine SIFT allows viewpoint difference between gallery face and probe face. Experiment results show our framework achieves better recognition accuracy than SIFT algorithm on FERET database.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.727-731
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• 2000

This paper presents a new practical autopilot design approach to acceleration control for tail-controlled STT(Skid-to-Turn) missiles. The approach is novel in that the proposed parametric affine missile model adopts acceleration as th controlled output and considers the couplings between the forces as well as the moments and control fin deflections. The aerodynamic coefficients in the proposed model are expressed in a closed form with fittable parameters over the whole operating range. The parameters are fitted from aerodynamic coefficient look-up tables by the function approximation technique which is based on the combination of local parametric models through curve fitting using the corresponding influence functions. In this paper in order to employ the results of parametric affine modeling in the autopilot controller design we derived a parametric affine missile model and designed a feedback linearizing controller for the obtained model. Stability analysis for the overall closed loop sys-tem is provided considering the uncertainties arising from approximation errors. the validity of the proposed modeling and control approach is demonstrated through simulations for an STT missile.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.547-555
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• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.4
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• pp.447-454
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• 2014

Recently most of functional synthesis methods for quantum circuit realization have a tendency to adopt the declarative functional expression more suitable for computer algorithms, so it's difficult to analysis synthesized quantum functions. This paper presents a new functional representation of quantum circuits compatible with simple architecture and intuitive thinking. The proposal of this paper is a new functional synthesis development by using the control functions as the power of corresponding to affine-controlled quantum gates based on the mathematical substitution of serial-product matrix operation over the target line for the arithmetic and modulo-2 ones between power functions of unitary operators. The functional synthesis algorithm proposed in this paper is useful for the functional expressions and synthesis using both of reversible and irreversible affine-controlled NCV-quantum gates.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.50 no.2
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• pp.195-206
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• 2017

Joint time-frequency images of the broadband echo signals of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution in controlled environments. Affine transformation and principal component analysis were used to obtain eigenimages that provided species-specific acoustic features for each of the six fish species. The echo images of an unknown fish species, acquired in real time and in a fully automated fashion, were identified by finding the smallest Euclidean or Mahalanobis distance between each combination of weight matrices of the test image of the fish species to be identified and of the eigenimage classes of each of six fish species in the training set. The experimental results showed that the Mahalanobis classifier performed better than the Euclidean classifier in identifying both single- and mixed-species groups of all species assessed.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.66-71
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• 2018

We propose an online parameter estimation method for surface-mounted permanent-magnet synchronous motor (SPMSM) using an affine projection algorithm (APA). The proposed method estimates parameters with two APAs based on the discrete-time model equation of SPMSM during motor operation. The first APA is designed to estimate inductance, and the second APA is designed to estimate resistance and flux linkage. However, in case when the d-axis current is controlled to 0A, the second APA cannot estimate resistance and flux linkage simultaneously because the matrix rank in APA becomes deficient. To overcome this problem, we temporarily inject a negative reference current input to the d-axis control loop, and the matrix in the APA then becomes full rank, which enables the simultaneous estimation of resistance and flux linkage. The proposed method is verified by PSIM simulation and an actual experiment, and the results reveal that SPMSM parameters can be estimated online during motor operation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.15-22
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• 2005

In this paper, we propose a PID-PD controller and its tuning method to be modified form of PID controller that consist of the affine set of PID and PI-PD controller by analyzing relation between these controllers. The proposed tuning method controls the closed-loop system to locate between the step responses of system controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost functions. Its effectiveness is examined by the case studies and their analysis.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.375-380
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• 2014

Under controlled environment, such as fixed viewpoints or consistent illumination, the performance of face recognition is usually high enough to be acceptable nowadays. Face recognition is, however, a still challenging task in real world. SIFT(Scale Invariant Feature Transformation) algorithm is scale and rotation invariant, which is powerful only in the case of small viewpoint changes. However, it often fails when viewpoint of faces changes in wide range. In this paper, we use Affine SIFT (Scale Invariant Feature Transformation; ASIFT) to detect affine invariant local descriptors for face recognition under wide viewpoint changes. The ASIFT is an extension of SIFT algorithm to solve this weakness. In our scheme, ASIFT is applied only to gallery face, while SIFT algorithm is applied to probe face. ASIFT generates a series of different viewpoints using affine transformation. Therefore, the ASIFT allows viewpoint differences between gallery face and probe face. Experiment results showed our framework achieved higher recognition accuracy than the original SIFT algorithm on FERET database.