• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.180-187
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• 2006

This paper presents a new sensor system, CALOS, for motion estimation and 3D reconstruction. The 2D laser sensor provides accurate depth information of a plane, not the whole 3D structure. On the contrary, the CCD cameras provide the projected image of whole 3D scene, not the depth of the scene. To overcome the limitations, we combine these two types of sensors, the laser sensor and the CCD cameras. We develop a motion estimation scheme appropriate for this sensor system. In the proposed scheme, the motion between two frames is estimated by using three points among the scan data and their corresponding image points, and refined by non-linear optimization. We validate the accuracy of the proposed method by 3D reconstruction using real images. The results show that the proposed system can be a practical solution for motion estimation as well as for 3D reconstruction.

• Journal of Biomedical Engineering Research
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• v.39 no.4
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• pp.153-160
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• 2018

3D ultrasound bladder scanners are getting popular in hospitals for the patients with bladder dysfunction. A current bladder scanner adopts a mechanical scan to acquire 3D images and requires two motors and complicated mechanical devices. In this paper, we propose a new ultrasound bladder scanner using hand-motion scan. Instead of two motors and mechanical devices, it has a motion sensor to record transducer positions during hand-motion scan. The experiments with a bladder phantom and volunteers showed similar measurement accuracy to a conventional 3D ultrasound bladder scanner. We expect that the proposed method will reduce the cost and size of the bladder scanner.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.9-12
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• 2002

In this Paper, we propose an efficient de-interlacing algorithm using temporal and spatial domain information. In the proposed scheme, motion estimation is performed same parity fields, i.e., if current field is even field, reference fields are previous even field and forward even field. And then motion vector refinement is performed to improve the accuracy of motion vectors. In the interpolating step, we use median filter to reduce the interpolation error caused by incorrect motion vector. Simulations conducted for various video sequences have shown the efficiency of the proposed interpolator with significant improvement over previous methods in terms of both PSNR and perceived image quality.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.810-813
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• 2007

Recently, mobile video communication is getting more and more popular. Visual quality and computational complexity are primary factors affecting performance of video communication. Frame rate up-conversion (FRC) is necessary for achieving high visual quality in mobile projection displays. In this paper, a FRC method using motion compensation based on block matching algorithm (BMA) with adaptive block size is proposed. In order to improve the accuracy of the estimated motion vectors, the motion vector refinement technique is proposed. Experiment results indicate that the proposed technique exhibits better performance with lower hardware complexity compared to the conventional methods.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.271-273
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• 2015

The bulk motion of star clusters can be determined after careful membership analysis using parametric or non-parametric approaches. This study aims to implement non-parametric membership analysis based on Binned Kernel Density Estimators which takes into account measurements errors (simply called BKDE-e) to determine the average proper motion of each cluster. This method is applied to 178 selected star clusters with angular diameters less than 20 arcminutes. Proper motion data from UCAC4 are used for membership determination. Non-parametric analysis using BKDE-e successfully determined the average proper motion of 129 clusters, with good accuracy. Compared to COCD and NCOVOCC, there are 79 clusters with less than $3{\sigma}$ difference. Moreover, we are able to analyse the distribution of the member stars in vector point diagrams which is not always a normal distribution.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.266-270
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• 1996

External linkage type spine motion analyzer was developed for measuring relative trunk motion respect to the pelvis. A special program for calculation of the relative angular motion and graphical display were also developed. The developed device assured its accuracy and conveniency after application to 15 normal volunteers and 18 patients after fixation and decompression surgery. Compare to the normal subjects, patients shows different angular motion especially in the angular acceleration.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.41-44
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• 1996

A new three step hierarchical search algorithm for motion estimation is proposed. The proposed algorithm exploits the motion correlation of spatially neighboring blocks and the motion continuity of temporally neighboring blocks to alleviate the local minimum problem in the first step of the three step hierarchical search algorithm (3SHS). Simulation results show that the proposed scheme achieves significant improvements in both estimation accuracy and performance reliability compared with the existing fast block matching algorithm including 3SHS, while maintaining almost the same computational complexity as 3SHS. The proposed scheme also possesses the regularity and simplicity of hardware-oriented features.

• Korean Journal of Applied Biomechanics
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• v.34 no.2
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• pp.71-80
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• 2024

Objective: This study aimed to explore the brain connectivity between brain and biomechanical variables by exploring motion recognition through FFT (fast fourier transform) analysis and AI (artificial intelligence) focusing on quiet standing movement patterns. Method: Participants included 12 young adult males, comprising university students (n=6) and elite gymnasts (n=6). The first experiment involved FFT of biomechanical signals (f_CoP, f_AJtorque and f_EEG), and the second experiment explored the optimization of AI-based GRU (gated recurrent unit) using f_EEG data. Results: Significant differences (p<.05) were observed in frequency bands and maximum power based on group and posture types in the first experiment. The second study improved motion prediction accuracy through GRU performance metrics derived from brain signals. Conclusion: This study delved into the movement pattern of upright standing posture through the analysis of bio-signals linking the cerebral cortex to motor performance, culminating in the attainment of motion recognition prediction performance.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.51-58
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• 2006

To compensate for the motion errors in hydrostatic tables, a method to actively control the clearance of a bearing corresponding to the amount of error using actively controlled capillaries is introduced in this paper. The design method for an actively controlled capillary that considers the output rate of a piezo actuator and the amount of error that must be corrected is described. The basic characteristics of such a system were tested, such as the maximum controllable range of the error, micro-step response, and available dynamic bandwidth when the capillary was installed in a hydrostatic table. The tests demonstrated that the maximum controllable range was $2.4\;{\mu}m$, the resolution was 27 nm, and the frequency bandwidth was 5.5 Hz. Simultaneous compensation of the linear and angular motion errors using two actively controlled capillaries was also performed for a hydrostatic table driven by a ballscrew and a DC servomotor. An iterative compensation method was applied to improve the compensation characteristics. Experimental results showed that the linear and angular motion errors were improved to $0.12{\mu}m$ and 0.20 arcsec, which were about $1/15^{th}$ and $1/6^{th}$ of the initial motion errors, respectively. These results confirmed that the proposed compensation method improves the motion accuracy of hydrostatic tables very effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4438-4460
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• 2017

The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.