• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.996-1002
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• 2015

In this paper, we present an effective system for the 3D scene labeling of objects from RGB-D videos. Our system uses a Markov Random Field (MRF) over a voxel representation of the 3D scene. In order to estimate the correct label of each voxel, the probabilistic graphical model integrates both scores from sliding window-based object detectors and also from object location prior maps. Both the object detectors and the location prior maps are pre-trained from manually labeled RGB-D images. Additionally, the model integrates the scores from considering the geometric constraints between adjacent voxels in the label estimation. We show excellent experimental results for the RGB-D Scenes Dataset built by the University of Washington, in which each indoor scene contains tabletop objects.

• 제어로봇시스템학회논문지
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• 제22권3호
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• pp.186-191
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• 2016

This paper addresses the development of 3D data acquisition system (3D scanner) based laser structured-light image. The 3D scanner consists of a stripe laser generator, a conventional camera, and a rotation table. The stripe laser onto an object has distortion according to 3D shape of an object. By analyzing the distortion of the laser stripe in a camera image, the scanner obtains a group of 3D point data of the object. A simple semiconductor stripe laser diode is adopted instead of an expensive LCD projector for complex structured-light pattern. The camera has an optical filter to remove illumination noise and improve the performance of the distance measurement. Experimental results show the 3D data acquisition performance of the scanner with less than 0.2mm measurement error in 2 minutes. It is possible to reconstruct a 3D shape of an object and to reproduce the object by a commercially available 3D printer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권9호
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• pp.1632-1652
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• 2011

This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes' particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes' particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

• 전자공학회논문지C
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• 제35C권1호
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• pp.55-63
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• 1998

This paper presents a new maching algorithm by Hopfield Neural Network for 3-D object recognition. In the proposed method, a model object is represented by a set of polygons in a single coordinate. And each polygon is described by a set of features; feature attributes. In case of 3-D object recognition, the scale and poses of the object are important factors. So we propose a strategy for 3-D object recognition independently to its scale and poses. In this strategy, the respective features of the input or the model objects are changed to the startegical constants when they are compared with one another. Finally, we show that the proposed method has a robustness through the results of experiments which included the classification of the input objects and the matching sequence to its 3-D rotation and scale.

• Journal of the Optical Society of Korea
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• 제15권3호
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• pp.264-271
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• 2011

In this paper we examine and compare the computational speeds of three-dimensional (3D) object recognition by use of digital holography based on central unit processing (CPU) and graphic processing unit (GPU) computing. The holographic fringe pattern of a 3D object is obtained using an in-line interferometry setup. The Fourier matched filters are applied to the complex image reconstructed from the holographic fringe pattern using a GPU chip for real-time 3D object recognition. It is shown that the computational speed of the 3D object recognition using GPU computing is significantly faster than that of the CPU computing. To the best of our knowledge, this is the first report on comparisons of the calculation time of the 3D object recognition based on the digital holography with CPU vs GPU computing.

• Journal of the Optical Society of Korea
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• 제11권3호
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• pp.108-112
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• 2007

Spectroscopic ellipsometry (SE) has become an important tool in scatterometry based nano-structure 3D profiling. In this paper, we propose a novel 3D nano object recognition method by use of phase sensitive scatterometry. We claims that only phase sensitive scatterometry can provide a reasonable 3D nano-object recognition capability since phase data gives much higher sensitive 3D information than amplitude data. To show the validity of this approach, first we generate various $0^{th}$ order SE spectrum data ($\psi$ and ${\Delta}$) which can be calculated through rigorous coupled-wave analysis (RCWA) algorithm and then we calculate correlation values between a reference spectrum and an object spectrum which is varied for several different object 3D shape.

• 로봇학회논문지
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• 제12권1호
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

• 한국전산구조공학회논문집
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• 제23권3호
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• pp.325-330
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• 2010

현행 토목 설계분야에서는 BIM(Building Information Modeling)기반의 3차원 객체모델의 활용이 미미한 수준이다. 본 논문에서는 철도교량의 상부구조인 PSC 박스거더에 대하여 BIM기반의 3차원 객체 모델을 구성하였으며, 모델의 기초구성은 파트(Part)모델로 되어있다. 파트(Part)모델은 여러 가지 단위 모델 중 최소 단위이며, 이것은 설계대상 구조물의 특성을 반영하여 계층구조를 가진다. 3차원 객체 모델은 설계자의 설계변경의도를 신속하게 반영할 수 있어야 한다. 실제 설계과정에서는 반복적인 설계변경이 발생할 수 있기 때문이다. 이를 위하여 설계변수를 파라미터로 구분을 하였으며 그 파라미터들은 3차원 객체모델의 정보와 연계되어 있기 때문에 설계 변경에 신속하게 대응할 수 있다. 이 연구에서 우리는 3차원객체 모델을 토목설계분야에 활용하여 얻을 수 있는 이점을 고찰하였다. 또한 PSC 박스거더의 3차원 객체 모델의 효율적인 적용방안을 제시하였다.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.963-968
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• 2007

본 논문에서는 현재 3D 그래픽뿐만 아니라 게임에서 정확한 충돌감지(collision-detection)나 컬링(culling)등은 3D공간에서 이러한 표준객체를 중심으로 많은 연구가 이루어지고 있다. 3D그래픽 분야에서 H/W의 놀라운 발달과 3D게임을 즐기는 게이머들이 좀 더 사실적인 표현에 깊은 관심을 가지고 있다. 90년대 중반 이후로 많이 연구되어진 3D 게임 엔진과 알고리즘 중에서 표준 3D 객체의 다양한 충돌 알고리즘을 분석하고, 기존의 3D 객체의 단순한 Hierarchies 구조에서 탈피하여 3D공간상에서 LOD(Level-of-Detail) 알고리즘을 이용하여, 3D객체가 3D 공간상에서 충돌검사의 성능을 향상시켜서 3D 게임의 필수 요소인 3차원 공간상의 효율적인 렌더링과 사실적인 표현의 알고리즘을 제안하여 실시간을 중요시 하는 3D 게임에서 사실감과 효율성을 높일 수 있게 제안한다.

• 한국정보통신학회논문지
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• 제6권4호
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• pp.632-638
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• 2002

확장할 수 있는 3D는 멀티미디어와 통합된 방송에 기초한 3D 콘텐츠와 상호 웹의 특징이 되는 소프트웨어의 기준이하고 할 수 있다 그런데, Web3d상에서 다각형의 polygon meshes을 처리하기에는 데이터의 크기나 실제에 적용하기에는 문제가 있다. 본 논문에서는 3차원 객체를 높은 품질로 표현하기 위해서 새로운 framework을 적용한다. 다양하고 자연스러운 형태의 표현을 위해 Web3D 자료형태를 VRML과 XML을 이용하여 처리한다. 3차원 객체의 polygon을 패한 구조를 정의하고 모델링 하여 타당성을 검증한다.