• 대한기계학회논문집A
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• 제26권12호
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• pp.2503-2510
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• 2002

Since the first shape-form-shading technique was developed by Horn in the early 1970s, many different approaches have been continuously emerging in the past three decades. Some of them improve existing techniques, while others are completely new approaches. Using the image reflectance equation, they estimate the 3-D shape of an object utilizing adequate constraints. Each algorithm applies different constraints such as brightness, smoothness, and integrability to solve the shape-from-shading problem. Especially for symmetric objects, a symmetry constraint is proposed to improve the performance of existing shape-from-shading algorithm in this paper. The symmetry constraint is imposed to a conventional algorithm and then the improvement in the performance of 3-D shape reconstruction is proved by quantitatively comparing the depth and gradient errors.

• 한국기계가공학회지
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• 제16권5호
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• pp.134-140
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• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• 한국통신학회논문지
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• 제19권10호
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• pp.1880-1893
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• 1994

본 논문에서는 한 장의 영상으로부터 물체의 형상을 복원하는shape from shading 문제에 접근하기 위한 새로운 알고리즘을 제안하였다. 제안된 반복 알고리즘에서 주어진 3차원 표면이 직교 다항식에 의해 근사화되고 주어진 표면과 그것이 미분치 사이의 관계를 다항식 개수를 이용한 행렬식으로 표현하였다. 또한 표면의 상대적인 높이와 그것이 미분치를 서로 반복적으로 갱신하면서 얻었다. 알고리즘의 성능을 밝기오차, 표면의 방향오차, 높이오차 측면에서 평가하였으며 제안된 방법과 기존의 여러 방법들과의 성능 비교를 보였다.

• 한국멀티미디어학회논문지
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• 제14권5호
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• pp.691-702
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• 2011

최근 컴퓨터 그래픽스와 사용자의 인지를 결합한 다양한 연구들이 진행되고 있다. Cole 등은 미술가들의 라인 드로잉 데이터를 수집하여 기존의 CG(Computer-Generated) 라인 드로잉 알고리즘들이 미술가들의 드로잉 특성을 반영하고 있는지 비교하고, 사용자들이 어떤 라인 드로잉 알고리즘의 결과에서 형태를 효과적으로 인지하는지 평가하는 실험을 수행하였다. 그러나 라인 드로잉 알고리즘의 결과보다 BRDF 쉐이딩 모델이 적용된 결과에서 형태를 더욱 효과적으로 인지한다는 결과를 보였는데, 이는 음영이 형태 정보를 전단하기에 더욱 효과적인 요소임을 반증한다. 따라서 본 논문에서는 물체에서 인지한 음영과 미술가들의 음영 표현, 그리고 CG 쉐이딩 알고리즘 간의 상관관계에 대해서 연구한다. 특히, 미술가들의 음영 표현 특성과 CG 쉐이딩 알고리즘에서 나타나는 특성에 초점을 맞추고 이를 정량적으로 분석한다. 본 논문에서 수집한 실험 데이터 및 분석 결과는 효과적인 형태 전달을 목적으로 하는 새로운 CG 쉐이딩 알고리즘을 설계하는데 활용한 것으로 기대된다.

• Journal of Computational Design and Engineering
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• 제3권2호
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• pp.121-131
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• 2016

Organic modeling of 3D characters is a challenging task when it comes to correctly modeling the anatomy of the human body. Most sketch based modeling tools available today for modeling organic models (humans, animals, creatures etc) are focused towards modeling base mesh models only and provide little or no support to add details to the base mesh. We propose a hybrid approach which combines geometrical primitives such as generalized cylinders and cube with Shape-from-Shading (SFS) algorithms to create plausible human character models from sketches. The results show that an artist can quickly create detailed character models from sketches by using this hybrid approach.

• 대한전자공학회논문지
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• 제27권6호
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• pp.972-981
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• 1990

Many researchers have been interested in whether complex computational problems can be solved by the neural net or not. Especially, problems of early vision are integrated by Tikhonov's regularization theory. Regularization technique can be realized in resistive net. In this paper, we suggest the resistive net with upper and lower thresholder to be able to compute shape from shading and to solve its discontinuous problem. We simulate three algorithms-Horn's algorithm, resistive net and up-low thrwsholding net -with respect to three cases-fully boundary, boundary losing partly and noisy image. As being able to cope with crease and discontinuous parts, we get the good 3D shape from shading.

• 대한전자공학회논문지
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• 제25권12호
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• pp.1532-1540
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• 1988

Shape from shading problem, such as other most early visions, is ill-posed problems, which can be solved by the use of regularization methods. This paper proposes the three kinds of stabilizer for the regularization. These are integrability constraints and spline functionals. Parallel iterative schemes are derived in the form of the finite difference approximation. Experimental results, show that the average error in surface orientation is less than 5%.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 1998년도 춘계학술발표논문집
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• pp.385-388
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• 1998

The main interest of previous researches for shape from shading was only on Lambertian surface which consists of diffuse reflectance surface. In practice, natural objects have hybrid reflectance, which limits the recovery of shape from intensity distribution[1][2]. In this paper, we propose the method of determining shape using neural network and diffuse illumination. The segmented region of sphere surface is used for training set, which can be determined by shadow line and edge of surface. Diffuse illumination is used to avoid specular spike and highlight which usually cause many problems such as intensity disparities. Diffuse illumination method using flat paper allows us to reduce these phenomena with simple scheme. Neural network and Diffuse illumination method are useful for shape from shading, because it can be applied to objects of unknown reflectance properties, but it is applied only to Torrance-Sparrow style reflectance.

• 한국CDE학회논문집
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• 제13권1호
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• pp.1-7
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• 2008

Data compression becomes increasingly an important issue for reducing data storage spaces as well as transmis-sion time in network environments. In 3D geometric models, the normal vectors of faces or meshes take a major portion of the data so that the compression of the vectors, which involves the trade off between the distortion of the images and compression ratios, plays a key role in reducing the size of the models. So, raising the compression ratio when the normal vector is compressed and minimizing the visual distortion of shape model's shading after compression are important. According to the recent papers, normal vector compression is useful to heighten com-pression ratio and to improve memory efficiency. But, the study about distortion of shading when the normal vector is compressed is rare relatively. In this paper, new normal vector compression method which is clustering normal vectors and assigning Representative Normal Vector (RNV) to each cluster and using the angular deviation from actual normal vector is proposed. And, using this new method, Visually Undistinguishable Lossy Compression (VULC) algorithm which distortion of shape model's shading by angular deviation of normal vector cannot be identified visually has been developed. And, being applied to the complicated shape models, this algorithm gave a good effectiveness.

• 전자공학회논문지B
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• 제33B권6호
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• pp.73-81
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• 1996

In this paper, based on the constrained optimizatin technique and direct recovery method, we proesent a shape form shading (SFS) algorithm to recover a 3-D shape form an image. More specifically, we first employ the membrane model for a smoothness constraint to revoer a 3-D shape coarsely. We then compute the surface height directly to reduce the shape distortion due to a regularization term. In our approach, we can obtain a stable and accurate solution by the application of these two steps. Several simulation results on various images are provided and discussed in this paper and they show that the proposed algorithm extracts the 3-D information accurately and efficiently.