• Journal of Computational Design and Engineering
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• 제2권1호
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• pp.67-72
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• 2015

Recently, along with the improvements of geometry modeling methods using sketch-based interface, there have been a lot of developments in research about generating surface model from 3D curves. However, surfacing a 3D curve network remains an ambiguous problem due to the lack of geometric information. In this paper, we propose a new algorithm for estimating the normal vectors of the 3D curves which accord closely with user intent. Bending energy is defined by utilizing RMF(Rotation-Minimizing Frame) of 3D curve, and we estimated this minimal energy frame as the one that accords design intent. The proposed algorithm is demonstrated with surface model creation of various curve networks. The algorithm of estimating geometric information in 3D curves which is proposed in this paper can be utilized to extract new information in the sketch-based modeling process. Also, a new framework of 3D modeling can be expected through the fusion between curve network and surface creating algorithm.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.

• 전자공학회논문지B
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• 제29B권1호
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• pp.1-10
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• 1992

This study presents a complete octree construction algorithm for 2D depth images obtained from orthogonal face views, which can represent 3D objects exactly. In constructing quadtree, optimal quadtree construction algorithm is applied to depth images for efficient use of memory and reduction of tree construction time. In addition, pseudo-octrees are constructed by using our proposed method, which construct pseudo-octrees according to the resolution value given in each node of constructed quadtree and mapping relation between quadrants and octants. Finally, a complete octree, which represents a 3D object, is constructed by volume intersection with each constructed pseudo-octree. The representation accuracy of a complete octree constructed by our algorithm is investigated by using a 3D display method and a volume ratio method for a complete octree.

• 한국콘텐츠학회논문지
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• 제6권11호
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• pp.302-309
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• 2006

본 논문에서는 3D 객체들의 재사용과 확장을 위해 실용적인 알고리즘을 제안하였다. 이 알고리즘은 Motion Path Modification rule에 바탕을 두고 있으며, 기존 3D 객체의 Motion을 재사용하여 새로운 Motion을 가진 3D객체를 재생성하여 사용하는데 있다. 논문에서 사용된 선형과 비선형 곡선 맞춤 알고리즘은 keyframe 보간에 의해 애니메이션을 수정하고 실제적인 움직임을 만드는데 적용된다. 본 논문에서는 또한 기존에 제작된 애니메이션의 세그먼트를 이용한 시나리오 기반 3D 이미지 합성시스템 프레임워크를 제안하였으며, 이 프레임워크는 기존에 만들어진 3D 객체 정보를 이용함으로써 게임 프로그래밍 및 시나리오 기반의 3D 애니메이션을 설계하는데 있어서 드는 많은 비용과 시간을 효율적으로 이용할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권1호
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• 정보처리학회논문지A
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• 제9A권2호
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• pp.217-224
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• 2002

3D 공간정보를 이용하여 3D 이미지를 처리하는 시스템이 많이 상용화되어 있다. 기존에 3D 이미지를 처리하기 위한 방법으로 고성능의 시스템을 이용하거나 이미지 압축 기술을 사용하였다. 하지만 고성능의 시스템을 사용하여 GIS 시스템을 구현할 경우 가격의 부담이 크다는 문제점이 있고 이미지 압축 기술을 사용하여 GIS 시스템을 구현할 경우 원 이미지에 손실이 크다는 문제점이 있다. 또한 일반 시스템에서 3D 이미지를 처리하려면 3D 이미지의 파일의 크기가 크기 때문에 공간 이미지를 처리하는데 시간이 오래 걸린다는 단점이 있다. 따라서 본 논문에서는 3D 이미지를 병렬로 처리하여 디스플레이 시간을 단축하는 병렬 알고리즘을 제안한다. 본 논문에서 제시된 병렬 알고리즘은 3D 이미지를 다수의 노드로 분할하여 각 노드에서 이미지를 화면에 디스플레이 하는 방법을 사용한다. 병렬컴퓨터의 노드의 수가 증가함에 따라 제안된 알고리즘의 성능이 증가함을 실험을 통해 보였다.

• 한국게임학회 논문지
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• 제3권2호
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• pp.24-29
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• 2003

The market of digital avatar with internet and digital technology is increasing rapidly. The users want to express any free-formed motion of their avatars in the cyber space. The user s motion capturing method as the avatar's motion can express any free-formed motion of the avatar in real-time but the methods are expensive and inconvenient. In this paper, we proposed a new method of expressing any free-formed motion of the avatar in real-time. The proposed method is an algorithm for real-time control of a 3D avatar in symmetry-formed free motion. Specially, the algorithm aims at the motion control of a 3D avatar for online dancing games. The proposed algorithm uses the skeleton character model and controls any one of two hands of the character model by a joystick with two sticks. In the symmetry-formed motion, the position and orientation of one hand can determine the position and orientation of the other hand. And the position and orientation of a hand as an end-effector can determine the pose of the arm by Inverse Kinematics. So the algorithm can control the symmetry-formed free motions of two arms by one joystick with two sticks. In the dance game, the algorithm controls the arm motion by the joystick and the other motion by the motion captured DB.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.139-142
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• 2000

$\mu$BGA(Ball Grid Array) is growing in response to a great demand for smaller and lighter packages for the use in laptop, mobile phones and other evolving products. However it is not easy to find its defect by human visual due to in very small dimension. From this point of view, we are interested its development of a vision based automated inspection algorithm. For this, first a 2D view of $\mu$BGA is described under a special blue illumination. Second, a notation-invariant 2D inspection algorithm is developed. Finally a 3D inspection algorithm is proposed for the case of stereo vision system. As a simulation result, it is shown that 3D defect not easy to find by 2D algorithm can be detected by the proposed inspection algorithm.

• 제어로봇시스템학회논문지
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• 제10권1호
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• pp.54-59
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• 2004

We suggest a 3D vision inspection algorithm which is based on the external shape feature. Because many electronic parts have the regular shape, if we have the database of pattern and can recognize the object using the database of the object s pattern, we can inspect many types of electronic parts. Our proposed algorithm uses the geometrical pattern matching method and 3D database on the electronic parts. We applied our suggested algorithm fer inspecting several objects including typical IC and capacitor. Through the experiments, we could find that our suggested algorithm is more effective and more robust to the inspection environment(rotation angle, light source, etc.) than conventional 2D inspection methods. We also compared our suggested algorithm with the feature space trajectory method.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.343-359
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• 2020

In this paper, a new algorithm is proposed for three-dimensional (3D) shape recognition using local features of model views and its sparse representation. The algorithm starts with the normalization of 3D models and the extraction of 2D views from uniformly distributed viewpoints. Consequently, the 2D views are stacked over each other to from view cubes. The algorithm employs the descriptors of 3D local features in the view cubes after applying Gabor filters in various directions as the initial features for 3D shape recognition. In the training stage, we store some 3D local features to build the prototype dictionary of local features. To extract an intermediate feature vector, we measure the similarity between the local descriptors of a shape model and the local features of the prototype dictionary. We represent the intermediate feature vectors of 3D models in the sparse domain to obtain the final descriptors of the models. Finally, support vector machine classifiers are used to recognize the 3D models. Experimental results using the Princeton Shape Benchmark database showed the average recognition rate of 89.7% using 20 views. We compared the proposed approach with state-of-the-art approaches and the results showed the effectiveness of the proposed algorithm.