• Journal of Korean Ophthalmic Optics Society
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• v.15 no.2
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• pp.169-174
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• 2010

Purpose: The purpose of this study is to evaluate the long-term stability of the improved symptoms and accommodative functions after completion of accommodative therapy. Methods: Seven children (mean age${\pm}$SD: $12{\pm}1.41$ years) who were successfully treated with a vision therapy program for either accommodative insufficiency or infacility were followed for 1 year. The visual symptoms of the subjects were measured by the College of Optometrists in Vision Development Quality of Life (COVD-QOL) checklist, and this was followed by measurement of the monocular and binocular accommodative facility with ${\pm}2.00$ D flipper lens. Results: The mean visual symptoms at the 1 year follow-up examination ($15.14{\pm}8.59$) showed a small increase, but there was no significant difference (p=0.446) from post-therapy ($11.86{\pm}7.22$). There was small regression in the monocular (left eye, $13.86{\pm}3.93cpm$) and binocular ($11.14{\pm}3.13cpm$) accommodative facility at the 1 year follow-up examination, but there were no significant different from the monocular ($15.86{\pm}4.14cpm$, p=0.147) and binocular ($13.21{\pm}3.76cpm$, p=0.066) accommodative facility measurements at post-therapy. Also, every subject met the normative values of ${\geq}7$ cpm for monocular accommodative facility and ${\geq}5$ cpm for binocular accommodative facility in the long-term. Conclusions: There was long-term maintenance of the improved visual symptoms and accommodative functions, and so it is clear that the positive therapeutic effects persist with accommodative therapy.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.98-108
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• 2008

Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (REFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.371-374
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• 1997

Recently, the development of computer achieves a system which is similar to the mechanics of human visual system. The 3-dimensional measurement using monocular vision system must be achieved a camera calibration. So far, the camera calibration technique required reference target in a scene. But, these methods are inefficient because they have many calculation procedures and difficulties in analysis. Therefore, this paper proposes a native method that without reference target in a scene. We use the grid type frame with different line widths. This method uses vanishing point concept that possess a rotation parameter of the camera and perspective ration that perspect each line widths into a image. We confirmed accuracy of calibration parameter estimation through experiment on the algorithm with a grid paper with different line widths.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.767-771
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• 2003

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. However, color information is useful for simple recognition in real-time visual servoing. In this paper, we refer to about object recognition using colors, stereo matching method, recovery of 3D space and the visual servoing.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.470-473
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• 1990

In this thesis, the recognition method of the movement of an 3D object is presented. The information about the movement of a 3D object is used to recognize the object. There are 2 kinds of movements which are translation and rotation. A difference picture is obtained from a sequence of images of a moving object or a scene which is taken by a monocular stationary observer. The 3D movement of an object is recognized by the Artificial Neural Network(ANN) using the difference picture.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.508-510
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• 2004

In this paper, we proposed the GPS position data correction method for autonomous land navigation using vanishing point property and a monocular vision system. Simulations are carried out over driving distances of approximately 60 km on the basis of realistic road data. In straight road, the proposed method reduces GPS position error to minimum more than 63% and positioning errors within less than 0.5m are observed. However, the average accuracy of the method is not presented. because it is difficult to estimate it in curve road or other road environments.

• ETRI Journal
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• v.40 no.4
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• pp.446-457
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• 2018

Robot navigation allows robot mobility. Therefore, mobility is an area of robotics that has been actively investigated since robots were first developed. In recent years, interest in personal service robots for homes and public facilities has increased. As a result, robot navigation within the home environment, which is an indoor environment, is being actively investigated. However, the problem with conventional navigation algorithms is that they require a large computation time for their building mapping and path planning processes. This problem makes it difficult to cope with an environment that changes in real-time. Therefore, we propose a humanoid robot navigation algorithm consisting of an image processing and optimization algorithm. This algorithm realizes navigation with less computation time than conventional navigation algorithms using map building and path planning processes, and can cope with an environment that changes in real-time.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.296-297
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• 2008

광섬유를 이용한 광스위치 연결작업에 있어서 페룰(Ferrule)면의 가공정도는 광커넥터 작업의 성패를 자우하는 매우 중요한 요소이다. 종래의 방법에서는 페룰면을 육안 검사나 현미경을 통한 확대 검사등의 방법을 사용하였고 자동화 검사의 경우도 절대적인 평탄도나 진원도를 나타내는 절대적인 값을 제시하고 있지 못한 단점이 있다. 이를 보완하기 위하여 카메라 입력단에 사각형의 기하 구조를 설치하고 이를 기준으로 영상을 전면에서 본 영상으로 변환하여 페룰면의 가공정도를 나타내주는 변수를 추출하는 새로운 방법을 제안하였다. 또한 실제 구현을 통하여 알고리즘의 강인성을 증명하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.241-243
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• 2010

Previous approaches to the 2D to 3D conversion problem require heavy computation or considerable amount of user input. In this paper, we propose a rather simple method in estimating the depth map from a single image using a monocular depth cue: haze. Using the haze imaging model, we obtain the distance information and estimate a reliable depth map from a single scenery image. Using the depth map, we also suggest an algorithm that converts the single image to 3D stereoscopic images. We determine a disparity value for each pixel from the original 'left' image and generate a corresponding 'right' image. Results show that the algorithm gives well refined depth maps despite the simplicity of the approach.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.197-205
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• 2014

As computer vision algorithms are developed on a continuous basis, the visual information from vision sensors has been widely used in the context of simultaneous localization and mapping (SLAM), called visual SLAM, which utilizes relative motion information between images. This research addresses a visual SLAM framework for online localization and mapping in an unstructured seabed environment that can be applied to a low-cost unmanned underwater vehicle equipped with a single monocular camera as a major measurement sensor. Typically, an image motion model with a predefined dimensionality can be corrupted by errors due to the violation of the model assumptions, which may lead to performance degradation of the visual SLAM estimation. To deal with the erroneous image motion model, this study employs a local bundle optimization (LBO) scheme when a closed loop is detected. The results of comparison between visual SLAM estimation with LBO and the other case are presented to validate the effectiveness of the proposed methodology.