• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.62-75
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• 2008

Vision-based simultaneous localization and map building using a single camera, while compelling in theory, have not until recently been considered extensive in the practical realm of the real world. In this paper, we propose a simple framework for the monocular SLAM of an indoor mobile robot using natural line features. Our focus in this paper is on presenting a novel approach for modeling the landmark before integration in monocular SLAM. We also discuss data association improvement in a particle filter approach by using the feature management scheme. In addition, we take constraints between features in the environment into account for reducing estimated errors and thereby improve performance. Our experimental results demonstrate the feasibility of the proposed SLAM algorithm in real-time.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.65-72
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• 2011

In this paper, a real-time monocular vision based navigation system is developed for the disabled people, where online background learning and vector field histogram are used for identifying obstacles and recognizing avoidable paths. The proposed system is performed by three steps: obstacle classification, occupancy grid map generation and VFH-based path recommendation. Firstly, the obstacles are discriminated from images by subtracting with background model which is learned in real time. Thereafter, based on the classification results, an occupancy map sized at $32{\times}24$ is produced, each cell of which represents its own risk by 10 gray levels. Finally, the polar histogram is drawn from the occupancy map, then the sectors corresponding to the valley are chosen as safe paths. To assess the effectiveness of the proposed system, it was tested with a variety of obstacles at indoors and outdoors, then it showed the a'ccuracy of 88%. Moreover, it showed the superior performance when comparing with sensor based navigation systems, which proved the feasibility of the proposed system in using assistive devices of disabled people.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.429-436
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• 2010

This paper presents a method to extract 3D outlines of objects in an image obtained from a monocular vision. After detecting the general outlines of the object by MOPS(Multi-Scale Oriented Patches) -algorithm and we obtain their spatial coordinates. Simultaneously, it obtains the space-coordinates with feature points to be immanent within the outlines of objects through SIFT(Scale Invariant Feature Transform)-algorithm. It grasps a form of objects to join the space-coordinates of outlines and SIFT feature points. The method which is proposed in this paper, it forms general outlines of objects, so that it enables a rapid calculation, and also it has the advantage capable of collecting a detailed data because it supplies the internal-data of outlines through SIFT feature points.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.187-193
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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. On a straight road, the proposed method reduces GPS position error by at least 63% within 0.5 m. However, the average accuracy of the method is not presented, because it is difficult to estimate it on other than a straight road in variable conditions.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.226-234
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• 2016

In this study, a model-referenced underwater navigation algorithm is proposed for high-precise underwater navigation using monocular vision near underwater structures. The main idea of this navigation algorithm is that a 3D model-based pose estimation is combined with the inertial navigation using an extended Kalman filter (EKF). The spatial information obtained from the navigation algorithm is utilized for enabling the underwater robot to navigate near underwater structures whose geometric models are known a priori. For investigating the performance of the proposed approach the model-referenced navigation algorithm was applied to an underwater robot and a set of experiments was carried out in a water tank.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.317-318
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• 2007

One of the important factors of the autonomous mobile robot is to build a map for surround environment and estimate its localization. This paper suggests a sensor fusion method of laser range finder and monocular vision sensor for the simultaneous localization and map building. The robot observes the comer points in the environment as features using the laser range finder, and extracts the SIFT algorithm with the monocular vision sensor. We verify the improved localization performance of the mobile robot from the experiment.

• Journal of Korean Ophthalmic Optics Society
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• v.14 no.3
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• pp.51-57
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• 2009

Purpose: The purpose of this study was to determine if monocular and binocular accommodative facility tests would be useful in diagnosing general binocular dysfunctions. Methods: 95 symptomatic children, who were selected from comprehensive vision tests, were classified into four groups (29 subjects with accommodative dysfunctions, 28 subjects with vergence dysfunctions, 25 subjects with combined accommodative and vergence dysfunctions, 13 subjects with normal binocular functions). Monocular and binocular accommodative facility was measured with ${\pm}$2.00 D flipper lenses. Results: Statistical analysis revealed that binocular accommodative facility measurement was significantly lower than monocular accommodative measurement in the vergence dysfunction group (p<0.01). However, there were no differences between monocular and binocular accommodative facility measurements in the group of accommodative or combined accommodative and vergence dysfunction (p>0.05). In addition, subjects with general binocular dysfunctions performed significantly poorer than subjects with normal binocular function on monocular and binocular accommodative facility (p<0.000). Conclusions: As a result of this study, monocular and binocular accommodative facility test, which could differentiate dysfunction from normal as well as between dysfunctions, indicated useful means for diagnosis of general binocular dysfunctions.

• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.977-987
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• 2023

The purpose of this study was to investigate the effect of visual information on the dynamic balance on Y-balance Test(YBT). The subjects of the study were 18 male and female adults in their 20s and 30s (age: 23.17±1.72 years, height: 172.46±9.84 cm, weight: 73.39±11.44 kg, leg length: 88.89±5.69 cm) who participated in the study. To measure dynamic balance between binocular and monocular use, absolute reach distance, composite score, and COP variables were measured on left and right feet through YBT and results were derived. As a result of the study, monocular block(left and right eye block) showed higher absolute reach and composite scores than binocular use in posterolateral, posteromedial, and composite scores during YBT. As a result of COP, there was no difference in anterior and posteromedial reach. When reaching posterolateral, AP COP velocity of left foot in monocular block appeared slower than that in binocular vision, and in COP velocity, COP velocity of left foot in monocular block appeared slower than binocular vision.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.1-11
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• 2013

The determination of the pose of the imaging camera is a fundamental problem in computer vision. In the monocular case, difficulties in determining the scene scale and the limitation to bearing-only measurements increase the difficulty in estimating camera pose accurately. Many mobile phones now contain inertial measurement devices, which may lend some aid to the task of determining camera pose. In this study, by means of simulation and real-world experimentation, we explore an approach to monocular camera localization that incorporates both observations of the environment and measurements from accelerometers and gyroscopes. The unscented Kalman filter was implemented for this task. Our main contribution is a novel approach to landmark initialization in a Kalman filter; we characterize the tolerance to noise that this approach allows.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1658-1667
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• 2008

Reconstruction of 3D objects from a single view image is generally an ill-posed problem because of the projection distortion. A monocular vision based 3D object localization method is proposed in this paper, which approximates an object on the ground to a simple bounding solid and works automatically without any prior information about the object. A spherical or cylindrical object determined based on a circularity measure is approximated to a bounding cylinder, while the other general free-shaped objects to a bounding box or a bounding cylinder appropriately. For a general object, its silhouette on the ground is first computed by back-projecting its projected image in image plane onto the ground plane and then a base rectangle on the ground is determined by using the intuition that touched parts of the object on the ground should appear at lower part of the silhouette. The base rectangle is adjusted and extended until a derived bounding box from it can enclose the general object sufficiently. Height of the bounding box is also determined enough to enclose the general object. When the general object looks like a round-shaped object, a bounding cylinder that encloses the bounding box minimally is selected instead of the bounding box. A bounding solid can be utilized to localize a 3D object on the ground and to roughly estimate its volume. Usefulness of our approach is presented with experimental results on real image objects and limitations of our approach are discussed.