• Journal of the Korean Society for Precision Engineering
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• v.27 no.11
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• pp.37-45
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• 2010

Stroke patients can't use their hands because of the paralysis of their fingers. Their fingers are recovered by rehabilitating training, and the rehabilitating extent can be judged by grasping a spherical object. At present, the used object in hospital is only a spherical object, and can't measure the force of fingers. Therefore, doctors judge the rehabilitating extent by touching and watching at their fingers. So, the spherical object measuring system which can measure the force of their fingers should be developed. In this paper, the finger-force measuring system with a six-axis force/moment sensor which can measure the spherical-object grasping force is developed. The six-axis force/moment sensor was designed and fabricated, and the force measuring device was designed and manufactured using DSP (digital signal processing). Also, the grasping force test of men was performed using the developed finger-force measuring system, it was confirmed that the average force of men was about 120N.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.238-245
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• 2010

Stroke patients can't use their hands because of the paralysis of their fingers. Their fingers are recovered by rehabilitating training, and the rehabilitating extent can be judged by grasping a spherical object. At present, the object used in hospital is only a spherical object, and can't measure the force of fingers. Therefore, doctors judge the rehabilitating extent by touching and watching at their fingers. So, the spherical object measuring system which can measure the force of their fingers should be developed. In this paper, the finger-force measuring system with a three-axis force sensor which can measure the spherical-object grasping force is developed. The three-axis force sensor is designed and fabricated, and the force measuring device is designed and manufactured using DSP(digital signal processing). Also, the grasping force test of men is performed using the developed finger-force measuring system, it was confirmed that the average force of men was about 120 N.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.92-99
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• 2002

To obtain visual information of a target object, a camera should be placed within the visibility region. As the visibility region is dependent on the relative position of the target object and the surrounding object, the position change of the surrounding object during a task requires recalculation of the visibility region. For a fast computation of the visibility region so as to modify the camera position to be located within the visibility region, we propose a spherical projection method. After being projected onto the sphere the visibility region is represented in $\theta$-$\psi$ spaces of the spherical coordinates. The reduction of calculation space enables a fast modification of the camera location according to the motion of the surrounding objects so that the continuous observation of the target object during the task is possible.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.625-628
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• 1999

In this paper, we consider the problem of finding the depth of a object in two images taken with cameras. For solving this problem, we introduce a spherical concave mirror model. First, a virtual concave mirror is assumed, and then a scene is obtained by camera at two different position which are on the surface of the mirror. The depth of object is calculated from two scenes by using the spherical-mirror equation. The algorithm has been tested on a real scene containing several objects, and showed that it is more useful for farther object.

• Journal of Korea Game Society
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• v.10 no.1
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• pp.157-165
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• 2010

This paper presents a novel real-time rendering algorithm based on spherical coordinate system of the object using convex hull. While OpenGL rendering pipeline touches all vertices of an object, the proposed method takes account the only visible vertices by examining the visible triangles of the object. In order to determine the visible areas of the object in its spherical coordinate representation, the proposed method uses 3D geometric relation of 6 plane equations of the camera frustum and the bounding sphere of the object. In addition, we compute the convex hull of the object and its maximum side factors for hidden surface removal. Simulation results showed that the quality of result image is almost same compared to original image and rendering performance is greatly improved.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.5-14
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• 2018

A lot of research has been done on image recognition technique for planar images and the performance has also been improved. However, it is difficult to recognize objects in spherical panoramic images or images in special form which are given in various environments because of the spherical distortion given in different form from the planar case. In this paper, we show that the neural network recognition approach can be used for object recognition in spherical image and suggest a method of using cubemap transform in order to increase recognition accuracy in spherical image.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.309-314
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• 2014

To generate a complete 3D model from depth images of multiple RGB-D cameras, it is necessary to find 3D transformations between RGB-D cameras. This paper proposes a convenient view calibration technique using a spherical object. Conventional view calibration methods use either planar checkerboards or 3D objects with coded-pattern. In these conventional methods, detection and matching of pattern features and codes takes a significant time. In this paper, we propose a convenient view calibration method using both 3D depth and 2D texture images of a spherical object simultaneously. First, while moving the spherical object freely in the modeling space, depth and texture images of the object are acquired from all RGB-D camera simultaneously. Then, the external parameters of each RGB-D camera is calibrated so that the coordinates of the sphere center coincide in the world coordinate system.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.850-853
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• 2017

In this paper, we propose an image analysis system based on omnidirectional image and object tracking image display using super wide angle camera. In order to generate spherical images, the projection process of converting from two wide-angle images to the equirectangular panoramic image was performed and the spherical image was expressed by converting rectangular to spherical coordinate system. Object tracking was performed by selecting the desired object initially, and KCF(Kernelized Correlation Filter) algorithm was used so that robust object tracking can be performed even when the object's shape is changed. In the initial dialog, the file and mode are selected, and then the result is displayed in the new dialog. If the object tracking mode is selected, the ROI is set by dragging the desired area in the new window.

• Journal of Korean Association for Spatial Structures
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• v.4 no.4 s.14
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• pp.77-84
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• 2004

Researches on spherical shell which is most usually applied have been completed by many investigators already and generalized numerical formula was derived. But the existent researches are limited to those on spherical shell with isotropic or orthotropic roof stiffness, periodic distribution of roof stiffness that can be caused by spherical and latticed roof system is not considered. Therefore, the object of this study is to develop a structural analysis program to analyze spherical shells that have periodicity of roof stiffness distribution caused by latticed roof of large space structure, grasp buckling characteristics and behavior of structure.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.89-96
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• 2019

360 degree 3-dimensional lidar sensors and vision cameras are commonly used in the development of autonomous driving techniques for automobile, drone, etc. By the way, existing calibration techniques for obtaining th e external transformation of the lidar and the camera sensors have disadvantages in that special calibration objects are used or the object size is too large. In this paper, we introduce a simple calibration method between two sensors using a spherical object. We calculated the sphere center coordinates using four 3-D points selected by RANSAC of the range data of the sphere. The 2-dimensional coordinates of the object center in the camera image are also detected to calibrate the two sensors. Even when the range data is acquired from various angles, the image of the spherical object always maintains a circular shape. The proposed method results in about 2 pixel reprojection error, and the performance of the proposed technique is analyzed by comparing with the existing methods.