• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.44-53
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• 2011

In this paper, we propose a 3D conversion algorithm of 2D video using depth layer partition method. In the proposed algorithm, we first set frame groups using cut detection algorithm. Each divided frame groups will reduce the possibility of error propagation in the process of motion estimation. Depth image generation is the core technique in 2D/3D conversion algorithm. Therefore, we use two depth map generation algorithms. In the first, segmentation and motion information are used, and in the other, edge directional histogram is used. After applying depth layer partition algorithm which separates objects(foreground) and the background from the original image, the extracted two depth maps are properly merged. Through experiments, we verify that the proposed algorithm generates reliable depth map and good conversion results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1168-1171
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• 2003

The visuo-motor map is based on the Kohonen's self-organizing map. The map is learned the relation of the end effecter coordinates and the joint angles. In this paper, a 3 d-o-fmanipulator which moves in the 2D space is targeted. A CCD camera is set beside the manipulator, and the end effecter coordinates are given from the image of a manipulator. As a result of learning, the end effecter can be moved to the destination without exact teaching.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.970-976
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• 2012

In this paper, a single LRF has been used to produce a 3D map for the mobile robot navigation. The 2D laser scanners are used for mobile robots navigation, where the laser scanner is applied to detect a certain level of area by the straight beam. Therefore it is limited to the usages of 2D obstacle detection and avoidance. In this research, it is designed to complement a mobile robot system to move up and down a single LRF along the yaw axis. During the up and down motion, the 2D data are stacked and manipulated to build a 3D map. Often a single LRF data are mixed with Gaussian and impulse noises. The impulse noises are removed out by the hybrid median filter designed in this research. The 2D data which are improved by deleting the impulse noises are layered to build the 3D map. Removing impulse noises while preserving the boundary is a main advantages of the hybrid median filter which has been used widely to improve the quality of images. The effectiveness of this hybrid median filter for rejecting the impulse noises has been verified through the real experiments. The performance of the hybrid median filter is evaluated in terms of PSNR (Peak Signal to Noise Ratio) and the processing time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.367-371
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• 2015

In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.

• Smart Structures and Systems
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• v.29 no.6
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• pp.777-783
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• 2022

Even though several deep learning-based methods have been applied in the field of acoustic source localization, the previous works have only been conducted using the two-dimensional representation of the beamforming maps, particularly with the planar array system. While the acoustic sources are more required to be localized in a spherical microphone array system considering that we live and hear in the 3D world, the conventional 2D equirectangular map of the spherical beamforming map is highly vulnerable to the distortion that occurs when the 3D map is projected to the 2D space. In this study, a 3D deep learning approach is proposed to fulfill accurate source localization via distortion-free 3D representation. A target function is first proposed to obtain 3D source distribution maps that can represent multiple sources' positional and strength information. While the proposed target map expands the source localization task into a point-wise prediction task, a PointNet-based deep neural network is developed to precisely estimate the multiple sources' positions and strength information. While the proposed model's localization performance is evaluated, it is shown that the proposed method can achieve improved localization results from both quantitative and qualitative perspectives.

• Biomedical Science Letters
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• v.2 no.1
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• pp.21-30
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• 1996

MAP kinases are a family of serine/threonine specific protein kinases becoming activated in response to different proliferative stimuli by phosphorylation at both threonine and tyrosine residue. Present study shows that MAP kinase was purified from P388 murine leukema cells by SP sephadex C-50, phenyl superose and Mono Q column chromatography and identified with anti-ERKl antibody by western blotting. Immnublotting analysis to the crude extract of P388 cell lysate shows 44 kD and other minor bands but partial purified fraction eluted from phenyl supherose column have 44kD and 66 kD isoform. Subcloned GST-fusion protein from N-terminal of $p56^{kk}$ was tested as a substrate for MAP kinase phosphorylation. It was showed that the wild type and mutant forms(S42A) were fully phosporylated by purified MAP kinase fraction as com-pare with the other mutant form(S59A). This finding suggest that those GST-fusion proteins may be used as substrate for the in vitro test of MAP kinase.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.368-378
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• 2015

3D conversion technology has been studied over past decades and integrated to commercial 3D displays and 3DTVs. The 3D conversion plays an important role in the augmented functionality of three-dimensional television (3DTV), because it can easily provide 3D contents. Generally, depth cues extracted from a static image is used for generating a depth map followed by DIBR (Depth Image Based Rendering) rendering for producing a stereoscopic image. However except some particular images, the existence of depth cues is rare so that the consistent quality of a depth map cannot be accordingly guaranteed. Therefore, it is imperative to make a 3D conversion method that produces satisfactory and consistent 3D for diverse video contents. From this viewpoint, this paper proposes a novel method with applicability to general types of image. For this, saliency as well as edge is utilized. To generate a depth map, geometric perspective, affinity model and binomic filter are used. In the experiments, the proposed method was performed on 24 video clips with a variety of contents. From a subjective test for 3D perception and visual fatigue, satisfactory and comfortable viewing of 3D contents was validated.

• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.271-277
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• 2006

In this study, we investigated the applicable plan of GIS on the environmental impact assessment of 60 Hz Powerline. So we assessed distance data based on calculations by use of 2D and 3D Geographical information systems(GIS) and distance data based on measurements on 1: 5000 maps accord with on site distance measurements to use input data for calculating magnetic field. One hundred eight of the on site measured addresses were selected from residences. The data were achieved by measuring the distance between residence and power line on maps with scales of 1: 5000. The digital map was obtained from National Geographic Information Institute with scales of 1: 5000, and we made 2D and 3D map. Correlation analyses were performed for statistical analyses. For the 3D GIS versus on site comparison of different exposure categories, 70 of 108 measurements were assigned to the correct category. Similarly for 2D GIS versus on site comparison, 71 of 108 were correctly categorized. When comparing map measurement with on site measurement, 62 of 108 were correctly categorized. When the correlation analysis was performed, best correlation was found between 3D GIS and on site measurements with r = 0.84947 (p<0.0001). The correlation between map and on site measurement yielded an r of 0.76517 (p<0.0001). Since the GIS measurements and map measurement were made from the center point in the building and the on site measurements had to be made from the closest wall on the building, this might introduce and additional error in urban areas. The difference between 2D and 3D calculations were resulted from the height of buildings.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.113-120
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• 2018

To fly a drone or unmanned aerial vechicle(UAV) safely, its pilot needs to maintain high situation awareness of its flight space. One of the important ways to improve the flight space awareness is to integrate both the global and the local navigation map a drone provides. However, the drone pilot often has to use the inconsistent reference frames or perspectives between the two maps. In specific, the global navigation map tends to display space information in the third-person perspective, whereas the local map tends to use the first-person perspective through the drone camera. This inconsistent perspective problem makes the pilot use mental rotation to align the different perspectives. In addition, integrating different dimensionalities (2D vs. 3D) of the two maps may aggravate the pilot's cognitive load of mental rotation. Therefore, this study aims to investigate the relation between perspective difference ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$) and the map dimensionality matches (3D-3D vs. 3D-2D) to improve the way of integrating the two maps. The results show that the pilot's flight space awareness improves when the perspective differences are smaller and also when the dimensionalities between the two maps are matched.

• Journal of the Ergonomics Society of Korea
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• v.23 no.1
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• pp.23-38
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• 2004

This study examines different types of navigation aids when a navigator performs target search tasks in Virtual Environments. The factors manipulated in this study include target information (None/Landmark). navigational difficulty (Easy/Difficult). and map types (None/2D Map/3D Map). Navigation performance was measured by using task completion time and the number of target locations that was remembered by the navigator. In addition, user satisfaction on the navigation aids was also measured by using a 7-point Likert's scale. The results showed that the user satisfaction on the landmark was high when the 3D Map was provided. The task completion time shortened when navigational difficulty was set at "easy." The number of remembered target locations was large when there was no landmark. It was also large with an easy navigation task. or a map (20 or 3D) provided. Guidelines for selecting navigation aids were proposed based on the results.