• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.220-221
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• 2011

본 논문에서는 스마트폰의 카메라와 플래시를 이용한 능동적 3차원 형상 취득 시스템을 제시한다. 두 대의 스마트폰을 이용하여 한 대의 스마트폰은 광원 역할과 광원 위치 추정을 위한 영상 취득을 하고 다른 스마트폰으로 고정된 위치에서 광원의 위치 변화에 따른 영상을 취득을 한다. 각 스마트폰에서 취득된 영상을 마커 기반에서 광원의 위치를 추정하고 카메라의 반응 함수에 의한 비선형적 왜곡과 렌즈의 왜곡을 보정한다. 광원의 방향 벡터와 보정된 영상의 밝기 값을 이용하여 photometric stereo 기법으로 3차원 형상을 취득한다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.5
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• pp.757-766
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• 1990

In this paper a new knowledge based vision system using orientation information on each surface of the 3-dimensional object is discussed. The measurement of the orientation information is performed by photometric stereo method. And then the obtained orientations are segmented using Gaussian curvature and mean curvature. A hierarchical knowledge base which is based on the characteristics, shape, area and length of the surface is built up, and then the knowledge based system infers by the condition interprete system (CIS). As the results, an easier and more accurate 3-D object recognition system is implemented, because it uses the characteristics and shapes as units of the surface in the recognition process.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1000-1005
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• 2007

본 논문에서는 실물체의 3차원 모델을 복원하기 위해 거리영상 카메라에서 획득된 3차원 점군에 대한 온라인 정합 기법을 제안한다. 제안하는 방법은 거리영상 카메라를 사용하여 연속된 거리영상과 사진영상을 획득하고 문턱값(threshold)을 이용하여 물체와 배경에 대한 정보를 분류한다. 거리영상에서 특징점을 선택하고 특징점에 해당하는 거리영상의 3차원 점군을 이용하여 투영 기반 정합을 실시한다. 초기정합이 종료되면 사진영상간의 대응점을 추적하여 거리영상을 정제하는 과정을 거치는데 대응점 추적에 사용되는 KLT(Kanade-Lucas-Tomasi) 추적기를 수정하여 초기정합의 결과를 대응점 탐색에 이용함으로써 탐색의 속도와 성공률을 증가시켰다. 특징점과 추적된 대응점에 해당하는 3차원 점군을 이용하여 거리영상의 정제를 수행하고 정합이 완료되면 오프라인에서 3차원 모델을 합성하였다. 제안한 알고리듬을 적용하여 2개의 실물체에 대하여 실험을 수행하고 3차원 모델을 생성하였다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.21-29
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• 1997

In this paper, we propose a new approach for recovering 3-D shape and extracting the reflectance properties of surface from intensity images. Photometric stereo method(PSM) is genrally based on the direct illumination. In this paper, the reflectance function is derived by interoduceing the indirect diffuse illumination in PSM and then applied to hybrid reflectance model which consists of two components; the lambertian and the specular reflectance. Under the hybrid reflectance model and the indirect diffuse illumination circumstance, the reflectance properties of sample surface can be extracting by normal sampler and then 3-D shape of an object can be recovered based on extracting reflectance properties. This method is rapid because of using the reference table and simplifies the restriction condition about the reflectance function existing in prior studies. Th erecovery efficiency in our method is better than that in prior studies. Also, this method is applied to various types of surfaces by defining general reflectance function.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.224-227
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• 2000

본 논문에서는 기준 영상으로부터 면의 반사특성을 검출하고, 구해진 반사특성을 임의의 물체에 적용하여 3매의 명암영상을 얻는다. 이 영상을 측광입체시법(photometric stereo method)에 적용하여 3차원 형상인식하는 방법을 제시한다. 본 연구에서 목적으로 하는 물체의 반사특성은 난반사(diffuse reflection)성분과 전반사(specular reflection)성분이 혼합된 혼합 반사면(hybrid reflectance surface)을 그 대상으로 하며, 이러한 면의 반사특성은 Torrance-sparrow모델로 가정하여 문제를 해결해 나간다. 본 연구에서 목적으로 하는 대상 물체는 동일한 재질로 이루어졌다는 가정 하에서 몇개의 표본점들을 취해 반복수치 계산하기 때문에 계산속도가 빠르며, 각 표본점들로부터 계산된 면특성 파라메터들의 평균값을 취해서 다시 Torrance-sparrow모델에 적용함으로써 측광입체시법의 해석을 가능토록 한다. 즉, 3차원 형상인식 과정시 계산된 면특성 파라메터를 사용해 생성한 참조표와 명암영상과의 비교에 의해 빠른 면방향 복구를 행할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.301-312
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• 1996

A new approach is presented for recovering the 3-D shape from shading image. Photometric Stereo Method (PSM) is generally based on the direct illumination. In this paper, the reflectance function is derived by introduceing the indirect diffuse illumination in PSM and then applied to hybrid reflectance model which consists fo two components; the Lambertian reflectance and the speclar reflectance. Under the hybrid reflectance model and the indirect diffuse illumination circumstances, the 3-D shape of object can be recovered from the suface normal vector extracted from the surface roughness, the surface reflectance ratio, and the intensity value of a pixel. This method is rapid because of using the reference table and simplifies the restriction condition about the reflectance function existing in prior studies. The recovery efficiency in our method is better than that in prior studies. Also, this method is applied to various types of surfaces by defining general reflectance function.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.493-502
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• 2007

An on-line registration technique is presented to register multi-view range images for the 3D reconstruction of real objects. Using a range camera, we first acquire range images and photometric images continuously. In the range images, we divide object and background regions using a predefined threshold value. For the coarse registration of the range images, the centroid of the images are used. After refining the registration of range images using a projection-based technique, we use a modified KLT(Kanade-Lucas-Tomasi) tracker to match photometric features in the object images. Using the modified KLT tracker, we can track image features fast and accurately. If a range image fails to register, we acquire new range images and try to register them continuously until the registration process resumes. After enough range images are registered, they are integrated into a 3D model in offline step. Experimental results and error analysis show that the proposed method can be used to reconstruct 3D model very fast and accurately.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.200-204
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• 2008

In this paper, to solve localization problem for out-door navigation of robotic vehicles, a particle filter based 3D object recognition framework that can estimate the pose of a building or its entrance is presented. A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.52-61
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• 1992

An iterative scheme for computing the three-dimensional position and the surface orientation of an opaque object from a singel shaded image is proposed. This method demonstrates that calculating the depth(distance) between the camera and the object from one shaded video image is possible. Most previous research works on $'Shape from Shading$' problem, even in the $'Photometric Stereo Method$', invoved the determination of surface orientation only. To measure the depth of an object, depth of the object, and the reflectance properties of the surface. Assuming that the object surface is uniform Lambertian the measured intensity level at a given image pixel*x,y0becomes a function of surface orientation and depth component of the object. Derived Image Irradiance Equation can`t be solved without further informations since three unknown variables(p,q and D) are in one nonlinear equation. As an additional constraints we assume that surface satisfy smoothness conditions. Then equation can be solved relaxatively using standard methods of TEX>$'Calculus of VariationTEX>$'. After checking the sensitivity of the algorithm to the errors ininput parameters, the theoretical results is tested by experiments. Three objects (plane, cylinder, and sphere)are used. Thees initial results are very encouraging since they match the theoretical calculations within 20$\%$ error in simple experiments.> error in simple experiments.