• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.05a
• /
• pp.255-255
• /
• 2004

일반적으로 10,000 rpm 이상의 고속, 고이송 가공이 수행되는 고속가공에서 절삭력의 급격한 증가는 치명적인 결과를 초래할 수 있다. 따라서 실제 가공에 앞서 NC code에 존재하는 에러 유무를 검출하고, 주어진 절삭 조건의 적합성을 사전에 검사하는 NC 모의 가공 시스템의 중요성이 점점 강조되고 있는 실정이다. 절삭 영역의 탐색에는 일반적으로 Z-map 방식이 사용되고 있다. Z-map 방식은 자료구조의 단순성과 완결성으로 인하여 계산속돈가 라르고 오류 발생의 가능성이 상대적으로 낮기 때문에 상용 CAM 시스템은 대부분 이 방식을 기반으로 하고 있다.(중략)

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.406-408
• /
• 2001

기본적인 투영기법인 평행투영, 원근투영 기법과 Octree 모델을 사용하여 임의의 시각방향에서 모델의 2차원 투영영상을 생성하고 노드표면을 시각방향으로 평행 투영하여 이들 벡터의 곱의 절대값을 사용하여 2차원 투영영상을 Pseudo gray로 표현해 본다. 또한 평행투영과 원근투영 하에서 2차원상의 모델에서 3차원 모델의 특징점을 찾을 수 있는 기법을 제안하고 두 개의 모델 영상에 적용해 증명해 보았다. 이 기법은 3차원 물체 인식에 중요한 정보로 유용하게 사용 될 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.10B
• /
• pp.1937-1945
• /
• 1999

In paper, we propose a 3D polygonal mesh simplification technique based on vertex clustering. The proposed method differentiates the size of each cluster according to the local property of a 3D object. We determine the size of clusters by considering the normal vector of triangles and the vertex distribution. The subdivisions of cluster are represented by octree. In this paper, we use the Harsdorff distance between the original mesh and the simplified one as a meaningful error value. Because proposed method adaptively determine the size of cluster according to the local property of the mesh, it has smaller error as compared with the previous methods and represent the small regions on detail. Also it can generate a multiresolution model and selectively refine the local regions.

• The Journal of Information Technology
• /
• v.7 no.4
• /
• pp.1-8
• /
• 2004

The depth information of 3D image lost by projecting 3D-object to 2D-screen for earning image. If depth information is restored and is used to recognize 3D-object, we can make the more effective recognition system. We often use shape from stereo algorithm in order to restore this information. In this paper, we suggest 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In this system, we use the moving vector of object to reduce matching time and In second matching step, the unknown input image is compared with the reference images, which is made with octree codes. Octree codes are used in volume-based representation of a three dimensional object. The result of simulation show that the proposed 3-D object recognition system provides satisfactory performance.

• Journal of the Korea Computer Graphics Society
• /
• v.23 no.3
• /
• pp.19-29
• /
• 2017

When a fixed-sized memory allocation method is used for sparse volume data, a considerable memory space is in general wasted, which becomes more serious for a large volume of high resolution. In this paper, in order to reduce such unnecessary memory consumption, we propose a volume representation method to store mostly voxels that represent valid information rather than all voxels in a fixed volume space. Then our method is compared with the conventional static memory allocation method, an octree-based representation, and a voxel hashing method in terms of memory usage and computation speed. In particular, we compare the proposed method and the voxel hashing method with respect to implementation of the GPU-based Marching Cubes algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.12A
• /
• pp.1974-1984
• /
• 1999

In this paper, we introduce a highly efficient data structure that effectively captures the multipath phenomenon needed for accurate propagation modeling and fast propagation prediction. The proposed object representation procedure is called 'circular representation (CR)' of microwave masking objects such as buildings, to improve over the conventional vector representation (VR) form in fast ray tracing. The proposed CR encapsulates a building with a circle represented by a center point and radius. In this configuration, the CR essentially functions as the basic building block for higher geometric structures, enhancing the efficiency more than when VR is used alone. The simulation results indicate that the proposed CR scheme reduces the computational load proportionally to the number of potential scattering objects while its hierarchical structure achieves about 50% of computational load reduction in the hierarchical octree structure.

• Journal of KIISE:Computer Systems and Theory
• /
• v.27 no.8
• /
• pp.691-700
• /
• 2000

The standard volume ray-tracing, optimized with octree, needs to repeatedly traverse hierarchical structures for each ray that often leads to redundant computations. It also employs the expensive 3D interpolation for producing high quality images. In this paper, we present a new ray-casting method that efficiently computes shaded colors and opacities at resampling points by traversing octree only once. This method traverses volume data in object-order, finds resampling points on slices incrementally, and performs resampling based on 2D interpolation. While the early ray-termination, which is one of the most effective optimization techniques, is not easily combined with object-order methods, we solved this problem using a dynamic data structure in image space. Considering that our new method is easy to implement, and need little additional memory, it will be used as very effective volume method that fills the performance gap between ray-casting and shear-warping.

• Journal of Internet Computing and Services
• /
• v.7 no.5
• /
• pp.135-145
• /
• 2006

This paper presents a novel approach to real-time recognition of 3D environment and objects for intelligent robots. First. we establish the three fundamental principles that humans use for recognizing and interacting with the environment. These principles have led to the development of an integrated approach to real-time 3D recognition and modeling, as follows: 1) It starts with a rapid but approximate characterization of the geometric configuration of workspace by identifying global plane features. 2) It quickly recognizes known objects in environment and replaces them by their models in database based on 3D registration. 3) It models the geometric details on the fly adaptively to the need of the given task based on a multi-resolution octree representation. SIFT features with their 3D position data, referred to here as stereo-sis SIFT, are used extensively, together with point clouds, for fast extraction of global plane features, for fast recognition of objects, for fast registration of scenes, as well as for overcoming incomplete and noisy nature of point clouds. The experimental results show the feasibility of real-time and behavior-oriented 3D modeling of workspace for robotic manipulative tasks.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.1_2
• /
• pp.1-14
• /
• 2006

Sort-last parallel rendering using a cluster of GPUs has been widely used as an efficient method for visualizing large- scale volume datasets. The performance of this method is constrained by load balancing when data parallelism is included. In previous works static partitioning could lead to self-balance when only task level parallelism is included. In this paper, we present a load balancing scheme that adapts to the characteristic of volume dataset when data parallelism is also employed. We effectively combine the hierarchical data structures (octree and BSP tree) in order to skip empty regions and distribute workload to corresponding rendering nodes. Moreover, we also exploit a 3D clustering method to determine visibility order and save the AGP bandwidths on each rendering node. Experimental results show that our scheme can achieve significant performance gains compared with traditional static load distribution schemes.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.3
• /
• pp.31-39
• /
• 2006

This paper presents a novel approach to real-time recognition of 3D environment and objects for various applications such as intelligent robots, intelligent vehicles, intelligent buildings,..etc. First, we establish the three fundamental principles that humans use for recognizing and interacting with the environment. These principles have led to the development of an integrated approach to real-time 3D recognition and modeling, as follows: 1) It starts with a rapid but approximate characterization of the geometric configuration of workspace by identifying global plane features. 2) It quickly recognizes known objects in environment and replaces them by their models in database based on 3D registration. 3) It models the geometric details the geometric details on the fly adaptively to the need of the given task based on a multi-resolution octree representation. SIFT features with their 3D position data, referred to here as stereo-sis SIFT, are used extensively, together with point clouds, for fast extraction of global plane features, for fast recognition of objects, for fast registration of scenes, as well as for overcoming incomplete and noisy nature of point clouds.