• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.153-155
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• 2004

This paper proposes a real-time approach on the rotational motion estimation and correction for the roll stabilization of the sight system. This method first estimates a rotation center by the least-mean square algorithm based on the motion vectors of some feature points. And, then, a rotation angle is searched for a best matching block between a reference block image and seccessive input images using MPC(maximum pixel count) matching criterion. Finally, motion correction is performed by the bilinear interpolation technique. Various computer simulations show that the estimation performance is good and the proposed algorithm is a real-time implementable one to the TMS320C6415(500MHz) DSP.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.46-48
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• 2004

This paper presents a simple method of rotational and translational motion estimation for digital image stabilization. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. And then translational motion can be estimated by the relation among movement of rotation center, rotation angle and translation movement. To show the effectiveness of our approach, the synthetic images are evaluated, resulting in better performance.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.175-191
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• 2003

An empirical Bayesian approach is discussed for estimation of characteristics from the two-way balanced rotation sampling design which includes U.S. Current Population Survey and Canadian Labor Force Survey as special cases. An empirical Bayesian estimator is derived for monthly effect under presence of two types of biases and correlations It is shown that the marginal distribution of observation provides more general correlation structure than that frequentist has assumed. Consistent estimators are derived for hyper-parameters in Normal priors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.605-613
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD (Head Mounted Display) to control the tele-operated vision system on the mobile robot. In the preexistence tele-operated vision system, a joystick was used to control the pan-tilt unit of the remote camera system. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image. The simple experiment is conducted to demonstrate the feasibility.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.360-362
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD(Head Mounted Display) using the feature points detection to control the tele-operated vision system on the mobile robot. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.20-26
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• 2021

In this paper, we studied the rotation angle estimation methods required for image alignment in an image recognition environment. In particular, a rotation angle estimation method applicable to a low specification embedded-based environment was proposed and compared with the existing method using complex moment. The proposed method estimates the rotation angle through similarity mathcing of the 1D projection profile along the radial axis after converting an image into polar coordinates. In addition, it is also possible to select a method of using vector sum of the projection profile, which more simplifies the calculation. Through experiments conducted on binary pattern images and gray-scale images, it was shown that the estimation error of the proposed method is not significantly different from that of complex moment-based method and requires less computation and system resources. For future expansion, a study on how to match the rotation center in gray-scale images will be needed.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.393-399
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• 2013

We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.247-257
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• 2013

A variety of practical problems can be addressed in the framework of rotation (successive) sampling. The present work presents a sample rotation pattern where sampling units are drawn on two successive occasions. The problem of estimation of population variance on current (second) occasion in two - occasion successive (rotation) sampling has been considered. A class of estimators has been proposed for population variance that includes many estimators as a particular case. Asymptotic properties of the proposed class of estimators are discussed. The proposed class of estimators is compared with the sample variance estimator when there is no matching from the previous occasion. Optimum replacement policy is discussed. Results are supported with the empirical means of comparison.

• Steel and Composite Structures
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• v.31 no.5
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• pp.427-435
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• 2019

The estimation of moment and rotation in steel rack connections could be significantly helpful parameters for designers and constructors in the initial designing and construction phases. Accordingly, Extreme Learning Machine (ELM) has been optimized to estimate the moment and rotation in steel rack connection based on variable input characteristics as beam depth, column thickness, connector depth, moment and loading. The prediction and estimating of ELM has been juxtaposed with genetic programming (GP) and artificial neural networks (ANNs) methods. Test outcomes have indicated a surpass in accuracy predicting and the capability of generalization in ELM approach than GP or ANN. Therefore, the application of ELM has been basically promised as an alternative way to estimate the moment and rotation of steel rack connection. Further particulars are presented in details in results and discussion.

• Journal of Sensor Science and Technology
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• v.26 no.6
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• pp.371-378
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• 2017

An accurate and robust estimation of center of rotation (CoR) using optical marker trajectory is crucial in human biomechanics. In this regard, the performances of the two prevailing least-squares methods, the Gamage and Lasenby (GL) method, and the Chang and Pollard (CP) method, are verified in this paper. While both methods are sphere-fitting approaches in closed form and require no tuning parameters, they have not been thoroughly verified by comparison of their estimation accuracies. Furthermore, while for both methods, results for stationary CoR locations are presented, cases for perturbed CoR locations have not been investigated for any of them. In this paper, the estimation performances of the GL method and CP method are investigated by varying the range of motion (RoM) and noise amount, for both stationary and perturbed CoR locations. The difference in the estimation performance according to the variation in the amount of noise and RoM was clearly shown for both methods. However, the CP method outperformed the GL method, as seen in results from both the simulated and the experimental data. Particularly, when the RoM is small, the GL method failed to estimate the appropriate CoR while the CP method reasonably maintained the accuracy. In addition, the CP method showed a considerably better predictability in CoR estimation for the perturbed CoR location data than the GL method. Accordingly, it may be concluded that the CP method is more suitable than the GL method for CoR estimation when RoM is limited and CoR location is perturbed.