• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.217-223
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• 2015

In order to predict the motions of a planing hull in waves, it is necessary to accurately estimate the force components acting on the hull such as the hydrodynamic force, buoyancy, and friction, as well as the wave exciting force. In particular, based on strip theory, hydrodynamic forces can be estimated by the summation of the forces acting on each cross-section of the hull. A non-linear strip method for planing hulls was mathematically developed by Zarnick, and his formula has been used to predict the vertical motions of prismatic planing hulls in regular waves. In this study, several improvements were added to Zarnick's formula to predict the vertical motions of warped planing hulls. Based on calm water model test results, the buoyancy force and moment correction coefficients were modified. Further improvements were made in the pile-up correction. Pile-up correction factors were changed according to variations of the deadrise angles using the results found in previous research. Using the same hull form, captive model tests were carried out in other recent research, and the results were compared with the present calculation results. The comparison showed reasonably good agreements between the model tests and present calculations.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.419-426
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• 2022

In this paper, we propose a method to improve the accuracy of 3D human pose estimation model in various move motions. Existing human pose estimation models have some problems of jitter, inversion, swap, miss that cause miss coordinates when estimating human poses. These problems cause low accuracy of pose estimation models to detect exact coordinates of human poses. We propose a method that consists of detection and correction methods to handle with these problems. Deep learning-based outlier detection method detects outlier of human pose coordinates in move motion effectively and rule-based correction method corrects the outlier according to a simple rule. We have shown that the proposed method is effective in various motions with the experiments using 2D golf swing motion data and have shown the possibility of expansion from 2D to 3D coordinates.

• Journal of IKEEE
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• v.24 no.1
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• pp.33-39
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• 2020

In this paper, we propose the design technique of the vehicle's load weight measuring system using tire pressure, which is one of the physical elements of tires. The proposed technique consists of four processes: noise correction by load and vibration, gas flow correction, data mixer and weight conversion. Noise correction by load and vibration eliminates noise that increases the tire's internal pressure due to external shocks and vibrations produced by the vehicle while it is in motion. In the gas flow correction process, the noise of the internal pressure of the tire is increased due to the temperature rise of the ground with respect to the data obtained through the noise correction process due to the load and vibration. In the data mixer process, the load and pressure on the tolerances the empty, median and the full load are classified according to the change in pressure of the tire that is delivered perpendicular to the tire in the event of cargo. In the weight conversion process, weight is expressed by weight through weight conversion algorithms using noise correction results by load and vibration and gas flow correction. The weight conversion algorithm calculates the weight conversion factor, which is the slope of the linear function with respect to the load and pressure change, and converts the weight. In order to evaluate the accuracy of the loading weight measurement system of the vehicle using the tire pneumatic system technique proposed in this paper, we propose the design technique of the vehicle's load weight measuring system using tire pressure, which is one of the physical elements of tires.. Noise correction results by load and vibration and gas flow data correction results showed reliable results. In addition, repeated weight precision test showed better weight accuracy than the standard value of 90% of domestic companies.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.418-428
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• 2002

In this paper, we propose a motion-adaptive de-interlacing method using motion compensated interpolation. In a conventional motion compensated method, a simple pre-filter such as line averaging is applied to interpolate missing lines before the motion estimation. However, this method causes interpolation error because of inaccurate motion estimation and compensation. In the proposed method, EBMF(Edge Based Median Filter) as a pre-filter is applied, and new matching method, which uses two same-parity fields and opposite-parity field as references, is proposed. For further improvement, motion correction filter is proposed to reduce the interpolation error caused by incorrect motion. Simulation results show that the proposed method provides better performance than existing methods.

• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.411-419
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• 2004

When the imaging object rotates in image plane during MRI scan, its rotation causes phase error and non-uniform sampling to MRI signal. The model of the problem including phase error non-uniform sampling of MRI signal showed that the MRI signals corrupted by rotations about an arbitrary center and the origin in image plane are different in their phases. Therefore the following methods are presented to improve the quality of the MR image which includes the artifact. The first, assuming that the angle of 2-D rotational motion is already known and the position of 2-D rotational center is unknown, an algorithm to correct the artifact which is based on the phase correction is presented. The second, in case of 2-D rotational motion with unknown rotational center and unknown rotational angle, an algorithm is presented to correct the MRI artifact. At this case, the energy of an ideal MR image is minimum outside the boundary of the imaging object to estimate unknown motion parameters and the measured energy increases when the imaging object has an rotation. By using this property, an evaluation function is defined to estimate unknown values of rotational angle at each phase encoding step. Finally, the effectiveness of this presented techniques is shown by using a phantom image with simulated motion and a real image with 2-D translational shift and rotation.

• Investigative Magnetic Resonance Imaging
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• v.4 no.1
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• pp.20-26
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• 2000

Gradient moment nulling techniques require the introduction of an additional gradient on each axis for each order of motion correction to be applied. The additional gradients introduce new constraints on the sequence design and increase the demands on the gradient system. The purpose of this paper is to demonstrate techniques for optimization of gradient echo gradient moment nulling sequences within the constraints of the gradient hardware. Flow compensated pulse sequences were designed and implemented on a clinical magnetic resonance imaging system. The design of the gradient moment nulling sequences requires the solution of a linear system of equations. A Mathematica package was developed that interactively solves the gradient moment nulling problem. The package allows the physicist to specify the desired order of motion compensation and the duration of the gradients in the sequence with different gradient envelopes. The gradient echo sequences with first, second, and third order motion compensation were implemented with minimum echo time. The sequences were optimized to take full advantage of the capabilities of the gradient hardware. The sequences were used to generate images of phantoms and human brains. The optimized sequences were found to have better motion compensation than comparable standard sequences.

• Journal of The Korean Society of Integrative Medicine
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• v.5 no.2
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• pp.83-90
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• 2017

Purpose : The purpose of this study was to investigate the correlation between shoulder gradient, range of motion of the neck, and subjective pain level of the potential risk group of smart-phone addiction. Methods : The subjects of this study were 90 women's who had potential risk of smart-phone addiction. VAS was used to measure subjectively pain intensity. Global Postural System was used to measure forward head posture. CROM was used to measure flexion, extension, lateral flexion of cervical range of motion. Results : The results of this study showed that was significant positive correlation between the both shoulder gradient, and cervical range of motion(p<.05). Statistically significant negative correlation between the VAS and left lateral flexion(p<.05). Conclusions : The difference between the gradient of both shoulders increased with the use of smart-phone addiction, and the cervical left lateral flexion decreased as the pain increased. This suggests that recognition on decrease of using smart phone and postural correction is necessary.

• Smart Media Journal
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• v.6 no.3
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• pp.49-56
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• 2017

Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.