• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.157-162
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• 2003

The 3D Image which embodies real object to 3D space of computer enables various geometrical analysis as well as visualization of complex 3D shape by giving sense for the real and cubic effect that can not be offered in 2D image. Human gives real object to same physical properties in 3D space imagination world of computer, and it is expected that this enables offering of various information by user strengthening interface between human-computer to observe object in real condition. In this study, formal style routine of 3D image creation applying digital photogrammetry was designed for more practical, highly trusty 3D image creation, and the system was emboded using object-oriented technique which strengthen user interface. Also, the discontinuity information about rock slope using 3D image is acquired that is orientation, persistence, spacing and aperture etc.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.299-302
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• 1995

Recently, we proposed a 3-D range-image measuring system for a slowly moving object by mechanically scanning a laser light beam emitted from a self mixing laser diode. In this paper, we introduced that every object moves along a straight line course, which is set diagonally against the semiconductor laser beam so that we can recognize each shape and size parameters of objects separately from the acquired 3-D range-image. We measured a square mesa on a square plane as an object. The measured velocity was 4.44mm/s and 4.63mm/s with an error of 0.56mm/s to 0.37mm/s. And thickness error of the mesa was 0.5mm to 0.6mm, which was obtained from the 3-D range-image of the standstill or moving object with thickness of 17.Omm.

• 디지털산업정보학회논문지
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• 제11권3호
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• 한국측량학회지
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• 제29권5호
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• pp.459-469
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• 2011

객체의 형상을 결정할 수 있는 요소는 크기, 경사도와 경사방향, 곡률, 기복변화, 요소간의 특성관계, 선 또는 면이 이루는 각, 특징점의 분포형태 등 매우 다양하다. 객체가 존재하는 공간은 3차원이지만 대부분의 경우 2차원 공간상에서 객체를 표현하고 이를 기반으로 객체인식을 수행하고 있다. 본 연구에서는 3차원 공간에서 객체의 형태를 판단하기 위한 방법을 제안하기 위하여 기존의 체인코드를 3차원으로 확장시켜 큐브형태의 연산자의 적용을 수행하였다. 일련의 코드로 생성되는 3D 체인코드를 분석하여 객체를 정형화하여 하향식 방법에 의한 객체 모델링의 기반이 될 수 있음을 보여 주었다. 또한 점 데이터 분할에 적용할 수 있으며 이는 라이다 데이터에 의한 모델링에 사용될 수 있다.

• 정보처리학회논문지B
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• 제8B권5호
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• pp.573-578
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• 2001

This research proposes a generalized local feature structure named "LSG(Local Surface Group) for model-based 3D object recognition". An LSG consists of a surface and its immediately adjacent surface that are simultaneously visible for a given viewpoint. That is, LSG is not a simple feature but a viewpoint-dependent feature structure that contains several attributes such as surface type. color, area, radius, and simultaneously adjacent surface. In addition, we have developed a new method based on Bayesian theory that computes a measure of how distinct an LSG is compared to other LSGs for the purpose of object recognition. We have experimented the proposed methods on an object databaed composed of twenty 3d object. The experimental results show that LSG and the Bayesian computing method can be successfully employed to achieve rapid 3D object recognition.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.426-429
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• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

• Journal of Information Display
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• 제10권1호
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• pp.6-15
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• 2009

In this paper, a new approach is proposed for the efficient generation of computer-generated holograms (CGHs) using the spatially redundant data on a 3D object and the novel look-up table (N-LUT) method. First, the pre-calculated N-point principle fringe patterns (PFPs) were calculated using the 1-point PFP of the N-LUT. Second, spatially redundant data on a 3D object were extracted and re-grouped into the N-point redundancy map using the run-length encoding (RLE) method. Then CGH patterns were generated using the spatial redundancy map and the N-LUT method. Finally, the generated hologram patterns were reconstructed. In this approach, the object points that were involved in the calculation of the CGH patterns were dramatically reduced, due to which the computational speed was increased. Some experiments with a test 3D object were carried out and the results were compared with those of conventional methods.

• 대한전자공학회논문지SP
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• 제41권2호
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• pp.11-22
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• 2004

겹쳐진 물체의 분리에 대한 기존의 연구들은 주로 모델기반 정합방법을 사용하고 있어서 적용가능물체가 2차원물체에 한정되었고, 모델물체의 수가 증가하면 정합과정에 소요되는 시간이 지수적으로 증가하는 문제를 갖는다. 이러한 문제를 해결하기 위해 본 논문에서는 곡면을 포함하는 3차원물체를 대상으로 물체에 대한 정보가 없는 상황에서도 가리는 물체를 찾아내는 알고리즘을 제시한다. 이 방법을 이용함으로써 겹쳐진 물체의 인식이 독립된 하나의 물체를 인식하는 문제로 단순화될 수 있다. 제안하는 알고리즘은 물체를 면의 결합으로 해석하고 면들은 경계선을 속성으로 표현된다. 3차원 물체의 겹침은 2차원 영상에서 면의 겹침으로 보여 지고 면의 겹침은 경계선의 교차로 나타나는 특성을 이용하여 겹침의 형태를 경계선의 형태로 일반화하여 분류하는 기법을 사용하였다. 면사이의 겹침 관계를 면특징 관계도를 이용하여 표현하기 위해 관계계수를 정의하였고 관계계수의 값은 겹침의 형태를 보여주도록 개념화하였다. 제안된 알고리즘의 성능은 산업현장에서 사용되는 표준 부품을 임의로 겹치게하여 영상을 획득한 후 가리는 물체를 구분하는 실험을 통해 입증하였다.

• 한국항행학회논문지
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• 제27권2호
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• pp.190-196
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• 2023

최근 들어, 라이다 기술의 발전에 따라 정확한 거리 측정이 가능해지면서 라이다 기반의 3차원 객체 탐지 네트워크에 대한 관심이 증가하고 있다. 기존의 네트워크는 복셀화 및 다운샘플링 과정에서 공간적인 정보 손실이 발생해 부정확한 위치 추정 결과를 발생시킨다. 본 연구에서는 고수준 특징과 높은 위치 정확도를 동시에 획득하기 위해 어텐션 기반 융합 방식과 카메라-라이다 융합 시스템을 제안한다. 먼저, 그리드 기반의 3차원 객체 탐지 네트워크인 Voxel-RCNN 구조에 어텐션 방식을 도입함으로써, 다중 스케일의 희소 3차원 합성곱 특징을 효과적으로 융합하여 3차원 객체 탐지의 성능을 높인다. 다음으로, 거짓 양성을 제거하기 위해 3차원 객체 탐지 네트워크의 탐지 결과와 이미지상의 2차원 객체 탐지 결과를 결합하는 카메라-라이다 융합 시스템을 제안한다. 제안 알고리즘의 성능평가를 위해 자율주행 분야의 KITTI 데이터 세트를 이용하여 기존 알고리즘과의 비교 실험을 수행한다. 결과적으로, 차량 클래스에 대해 BEV 상의 2차원 객체 탐지와 3차원 객체 탐지 부분에서 성능 향상을 보였으며 특히 Voxel-RCNN보다 차량 Moderate 클래스에 대하여 정확도가 약 0.47% 향상되었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.