• Journal of Information Display
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• v.10 no.1
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• pp.1-5
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• 2009

A novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. The intensity values are aggregated to determine the correct depth plane of each plane object. The experimental and simulation results show that the reconstructed depth image on the incorrect depth plane is effectively suppressed, and that the depth image on the correct depth plane is reconstructed clearly without any noise. The correct depth plane is also exactly determined.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1334-1337
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• 2009

The human vision system has visual functions for viewing 3D images with a correct depth. These functions are called accommodation, vergence and binocular stereopsis. Most 3D display system utilizes binocular stereopsis. The authors have developed a monocular 3D vision system with accommodation mechanism, which is useful function for perceiving depth.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.368-372
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• 2009

Pin-hole model has been widely used as a robust tool for easily understanding how to obtain a stereo image and how to present the depth-cue to an observer in stereoscopy. However, most of the processes to analyze depth cue in stereoscopy are performed that a stereo image is taken by camera model practically but depth cue of the image is analyzed by pin-hole model. Therefore, the result of depth cues by the process to be uncorrected. The reason of the uncorrected depth cue is led to the image distances of camera model due to variable focused object distances, and it makes a depth distortion. In this paper, we tried to show the contradiction such as occurring depth distortion in the process which the pin-hole model is used to analyze depth cue despite practical camera model is used in stereoscopy, and we presents the method to overcome the contradiction.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.606-613
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• 2017

When the planar area is captured by the depth camera, the shape of the plane in the captured image has perspective projection distortion according to the position of the camera. We can correct the distorted image by the depth information in the plane in the captured area. Previous depth information based perspective distortion correction methods fail to satisfy the real-time property due to a large amount of computation. In this paper, we propose the method of applying the conversion table selectively by measuring the motion of the plane and performing the correction process by parallel processing for correcting perspective projection distortion. By appling the proposed method, the system for correcting perspective projection distortion correct the distorted image, whose resolution is 640x480, as 22.52ms per frame, so the proposed system satisfies the real-time property.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.11-17
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• 2016

In this paper, we propose a method of correcting depth image by the plane modeling and then improving the coding performance. We model a plane by using the least squares method to the horizontal and vertical directions including the target pixel, and then determine that the predicted plane is suitable from the estimate error. After that, we correct the target pixel by the plane mode. The proposed method can correct not only the depth image composed the plane but also the complex depth image. From the simulation result that measures the entropy power, which can estimate the coding performance, we can see that the coding performance by the proposed method is improved up to 80.2%.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.39-42
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• 2008

We have developed new display techniques that allow presentation of nearly correct focus cues. Using these techniques, we find that stereo vision is faster and more accurate, and that viewers experience less discomfort, when focus cues are consistent with simulated depth.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.10a
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• pp.293-298
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• 2001

N-value is usually used to assume the displacement depth of embankment on the soft marine clay. But N-value of the soft marine clay tend to underestimate unlike overestimating of general cases. In general case, if the length of rod is more long then N-value is more large because it is under the influence of energy loss of hammer blow. So it is reasonable to correct N-value down. But in the case of soft marine clay, N-value must not be correct down. Especially to assume the displacement depth of embankment on the soft marine clay, it must be used laboratory test results or CPT, Vane Test than N-value. In this study, it is compared with two field cases that design displacement method of embankment.

• Korean Journal of Optics and Photonics
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• v.18 no.4
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• pp.246-255
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• 2007

The floating image system (FIS) is a device to display input source in the space between fast surface of the display and an observer and it provides pseudo 3D depth to an observer when input source as real object or 2D image was displayed through the optical lens system in the FIS. The Advanced floating image system (AFIS) was designed to give more effective 3D depth than existing FIS by adding front and rear depth cues to the displayed stereogram, which it was used as input source. The magnitude of disparity and size of stereogram were strongly related each other and they have been optimized for presenting 3D depths in a non-optical lens systems. Thus, if they were used in optical lens system, they will have reduced or magnified parameters, leading to problem such as providing incorrect 3D depth cues to an observer. Although the size of stereogram and disparity were demagnified by total magnifying power of optical system, the viewing distance (VD) from the display to an observer and base distance (BD) for the gap between the eyes were fixed. For this reason, the quantity of disparity in displayed stereogram through the existing FIS has not kept the magnifying power to the total optical system. Therefore, we proposed the methods to provide correct 3D depth to an observer by compensating quantity of disparity in stereogram which was satisfied to keep total magnifying power of optical lenses system by AFIS. Consequently, the AFIS provides a good floating depth (pseudo 3D) with correct front and rear 3D depth cues to an observer.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.43-50
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• 2017

In this paper, we propose a method which detects the nose and face of certain human by using the depth image. The proposed method has advantages of the low computational complexity and the high accuracy even in dark environment. Also, the detection accuracy of nose and face does not change in various postures. The proposed method first locates the locally protruding part from the depth image of the human body captured through the depth camera, and then confirms the nose through the depth characteristic of the nose and surrounding pixels. After finding the correct pixel of the nose, we determine the region of interest centered on the nose. In this case, the size of the region of interest is variable depending on the depth value of the nose. Then, face region can be found by performing binarization using the depth histogram in the region of interest. The proposed method can detect the nose and the face accurately regardless of the pose or the illumination of the captured area.