• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.537-542
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• 2011

A mirror neuron is a neuron fires both when an animal acts and when the animal observes the same action performed by another. We propose a method of 3D reconstruction for occluded object motion tracking like Mirror Neuron System to fire in hidden condition. For modeling system that intention recognition through fire effect like Mirror Neuron System, we calculate depth information using stereo image from a stereo camera and reconstruct three dimension data. Movement direction of object is estimated by optical flow with three-dimensional image data created by three dimension reconstruction. For three dimension reconstruction that enables tracing occluded part, first, picture data was get by stereo camera. Result of optical flow is made be robust to noise by the kalman filter estimation algorithm. Image data is saved as history from reconstructed three dimension image through motion tracking of object. When whole or some part of object is disappeared form stereo camera by other objects, it is restored to bring image date form history of saved past image and track motion of object.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.150-161
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• 2013

This paper presents a new system which produces high resolution 3D contents by capturing multiview images of an object using multiple cameras, and estimating geometric and texture information of the object from the captured images. Even though a variety of multiview image-based 3D reconstruction systems have been proposed, it was difficult to generate high resolution 3D contents because multiview image-based 3D reconstruction requires a large amount of memory and computation. In order to reduce computational complexity and memory size for 3D reconstruction, the proposed system predetermines the regions in input images where an object can exist to extract object boundaries fast. And for fast computation of a visual hull, the system represents silhouettes and 3D-2D projection/back-projection relations by chain codes and 1D homographies, respectively. The geometric data of the reconstructed object is compactly represented by a 3D segment-based data format which is called DoCube, and the 3D object is finally reconstructed after 3D mesh generation and texture mapping are performed. Experimental results show that the proposed system produces 3D object contents of $800{\times}800{\times}800$ resolution with a rate of 2.2 seconds per frame.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.26-34
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• 2008

The information of traversability and path planning is essential for UGV(Unmanned Ground Vehicle) navigation. Such information can be obtained by analyzing 3D terrain. In this paper, we present the method of 3D terrain modeling with color information from a camera, precise distance information from a 2D Laser Range Finder(LRF) and wheel encoder information from mobile robot with less data. And also we present the method of 3B terrain modeling with the information from GPS/IMU and 2D LRF with less data. To fuse the color information from camera and distance information from 2D LRF, we obtain extrinsic parameters between a camera and LRF using planar pattern. We set up such a fused system on a mobile robot and make an experiment on indoor environment. And we make an experiment on outdoor environment to reconstruction 3D terrain with 2D LRF and GPS/IMU(Inertial Measurement Unit). The obtained 3D terrain model is based on points and requires large amount of data. To reduce the amount of data, we use cubic grid-based model instead of point-based model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.133-140
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• 2005

This paper presents a rapid face shape acquisition system. The system is composed of two cameras and one projector. The technique works by projecting a pattern on the object and capturing two images with two cameras. We use a 'one shot' system which provides 3D data acquired by single image per camera. The system is good for rapid data acquisition as our purpose. We use the 'absolutely coded pattern' using the hue and saturation of pattern lines. In this 'absolutely coded pattern' all patterns have absolute identification numbers. We solve the correspondence problem between the two images by using epipolar geometry and absolute identification numbers. In comparison to the 'relatively coded pattern' which uses relative identification numbers, the 'absolutely coded pattern' helps obtain rapid 3D data by one to one point matching on an epipolar line. Because we use two cameras, we obtain two images which have similar hue and saturation. This enables us to have the same absolute identification numbers in both images, and we can use the absolutely coded pattern for solving the correspondence problem. The proposed technique is applied to face data and the total time for shape acquisition is estimated.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.303-315
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• 2007

This paper proposes a 3D structure recovery and registration method that uses four or more common points. For each frame of a given video, a partial structure is recovered using tracked points. The 3D coordinates, camera positions and camera directions are computed at once by our improved scaled orthographic factorization method. The partially recovered point sets are parts of a whole model. A registration of point sets makes the complete shape. The recovered subsets are integrated by transforming each coordinate system of the local point subset into a common basis coordinate system. The process of shape recovery and integration is performed uniformly and linearly without any nonlinear iterative process and without loss of accuracy. The execution time for the integration is significantly reduced relative to the conventional ICP method. Due to the fast recovery and registration framework, our shape recovery scheme is applicable to various interactive video applications. The processing time per frame is under 0.01 seconds in most cases and the integration error is under 0.1mm on average.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.436-443
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• 1999

Most of the 3D object reconstruction techniques divide the object into multiplane and approximate the surfaces of the object. The Marching Cubes Algorithm which initializes the mesh structure using a given isovalue. and Delaunay Tetrahedrisation are widely used. Deformable models are well-suited for general object reconstruction because they make little assumptions about the shape to recover and they can reconstruct objects *om various types of datasets. Now, many researchers are studying the reconstruction systems based on a deformable model. In this paper, we propose a novel method for reconstruction of 3D objects. This method, for a 3D object composed of curved planes, compresses the 3D object based on the adaptive simplexmesh technique. It changes the pre-defined mesh structure, so that it may approach to the original object. Also, we redefine the geometric characteristics such as curvatures. As results of simulations, we show reconstruction of the original object with high compression and concentration of vertices towards parts of high curvature in order to optimize the shape description.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.435-448
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• 2008

3D posture recognition is a solution to overcome the limitation of 2D posture recognition. There are many researches carried out for 3D posture recognition using 3D data. The 3D data consist of massive surface points which are rich of information. However, it is difficult to extract the important features for posture recognition purpose. Meanwhile, it also consumes lots of processing time. In this paper, we introduced a dimension reduction method that transform 3D surface points of an object to 2D data representation in order to overcome the issues of feature extraction and time complexity of 3D posture recognition. For a better feature extraction and matching process, a cylindrical boundary is introduced in meshless parameterization, its offer a fast processing speed of dimension reduction process and the output result is applicable for recognition purpose. The proposed approach is applied to hand and human posture recognition in order to verify the efficiency of the feature extraction.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.395-401
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• 2003

다목적 대형 댐의 건설로 수몰된 과거의 삶의 공간을 20년이 지나서 다시 복원한다는 것은 그곳에 살던 실향민 등에게는 참으로 반가운 소식이다. 본 연구에서는 1980년대 초에 완공된 충주댐으로 인하여 물 속에 잠긴 청풍지구를 수몰이전의 입체 지형 공간적으로 원형복원하기 위한 원격탐사 기법을 적용한 것이다. 비교적 해상도가 좋은 인공위성 사진자료와 댐 수몰이전의 디지털 위성영상 데이터를 수집하고, 수몰직전에 제작된 지형도를 이용하여 위성영상자료의 통합 적용하여 수몰직전의 지형공간정보를 현재시간으로 영상 복원하기 위하여 원격탐사 기법을 적용한 것이다 이를 위하여 지형도에서 추출한 등고선과 현재의 등고선과의 접목을 통하여 청풍 주변지역을 중심으로 당시의 수치표고모형을 생성하였다. 또한 이를 입체적으로 보여주기 위한 투시조감도를 각 방향에서 생성함으로서 수몰이전의 아름다운 모습을 3차원적으로 영상복원 하였다. 또한 좀더 가까이서 수몰마을을 보기 위한 근접비행시뮬레이션 동영상을 제작하여 과거 기억 속의 고향을 영상에서 찾아볼 수 있도록 한 것이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.325-326
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• 2023

본 논문은 2차원적인 이미지를 모델링 하여, 대한민국의 보물 제750호이자 오래된 거돈사지 삼층석탑의 복원과 구현을 위한 연구이다. 기존 2D 이미지를 벗어나 문화재의 특성상 3D 형태의 복원이 적합하여 연구를 진행하였다. 문화재 복원은 자료와 전문가의 기술 및 역사적인 기록물 자료에 의존해 복구한다. 최근 인공지능 및 기술의 발달로 문화재 정보를 바탕으로 한 3차원 기술을 사용하여 다양한 데이터들과 프로그램을 이용한 모델링이 가능하다. 본 연구는 거돈사지 삼층석탑의 복원이 실제적이고도 구체적인 다각도의 방향에서 더 정밀하고 정확하게 도출하는데 기여할 것으로 기대된다.

• Broadcasting and Media Magazine
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• v.25 no.2
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• pp.17-26
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• 2020

최근 스마트폰에서의 증강현실, 미적 효과의 증대(예, 라이브 포커싱) 등의 어플리케이션을 제공하기 위해 모바일 기기에서의 3차원 공간 복원 기술에 대한 관심이 증가하고 있다. 소비자들의 요구에 발 맞춰 최근 스마트폰 제조사는 모든 플래그십 모델에 다중 카메라 및 뎁스 센서(거리 측정 센서)를 탑재하는 추세이다. 본 고에서는 모바일 폰에 탑재되고 있는 대표적인 세 축의 뎁스 추정(공간 복원) 방식에 대해 간단히 살펴보고, 최근 심층학습(Deep learning)의 등장으로 기술 발전의 새로운 국면에 접어 든 다중 시점 매칭(Multi-view stereo) 방법에 대해 소개하고자 한다. 심층 신경망이 재조명 받은 2012년 전까지 주류 연구 방향이었던 전통 기하학 기반의 방법에 대한 소개를 시작으로 심층 신경망기반의 방법론으로의 발전된 형태를 살펴본다. 또한, 신경망기반의 방법론은 크게 3 세대로 나누어 각 세대별 특징에 대해 자세히 살펴보고, 다양한 데이터에 대한 실험 결과를 통해 세대별 공간 복원 결과를 비교 분석한다.