• Title/Summary/Keyword: 컨벡스헐 알고리즘

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Approximating the Convex Hull for a Set of Spheres (구 집합에 대한 컨벡스헐 근사)

  • Kim, Byungjoo;Kim, Ku-Jin;Kim, Young J.
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.1
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    • pp.1-6
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    • 2014
  • Most of the previous algorithms focus on computing the convex hull for a set of points. In this paper, we present a method for approximating the convex hull for a set of spheres with various radii in discrete space. Computing the convex hull for a set of spheres is a base technology for many applications that study structural properties of molecules. We present a voxel map data structures, where the molecule is represented as a set of spheres, and corresponding algorithms. Based on CUDA programming for using the parallel architecture of GPU, our algorithm takes less than 40ms for computing the convex hull of 6,400 spheres in average.

Radiosity Rendering System Implementation using Incremental Convex Hull Algorithm (인크리먼털 컨벡스 헐 알고리즘을 이용한 래디오시티 렌더링 시스템 구현)

  • 김종용;최성희;송주환;최임석;권오봉
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.562-564
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    • 1999
  • 래디오시티 렌더링 시스템에 적합한 모델링을 하는데 있어서 수작업을 비롯한 기존의 여러 방법을 적용해 본 결과, 제작하고자 하는 환경 설정에 많은 어려움을 겪었다. 본 논문은 이러한 문제를 해결하기 위해, 인크리먼털 컨벡스 헐 모델링 기법을 응용하여 시스템을 개발하였다. 이 시스템은 기본 데이터 정보를 입력하면 자동적으로 패치와 엘리먼트가 생성되는 프로그램으로, 물체가 많은 환경이나 곡면을 비교적 쉽고, 고속으로 표현할 수 있었다. 그리고 인크리먼털 컨벡스 헐 알고리즘으로 생성된 환경에, 폼 팩터의 대표적인 세 가지 알고리즘들을 비교.평가 해본 결과 Cubic-Tetrahedron 알고리즘이 가장 효율적이었음을 알 수 있었다.

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Building Boundary Reconstruction from Airborne Lidar Data by Adaptive Convex Hull Algorithm (적응적 컨벡스헐 알고리즘을 이용한 항공라이다 데이터의 건물 경계 재구성)

  • Lee, Jeong-Ho;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.3
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    • pp.305-312
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    • 2012
  • This paper aims at improving the accuracy and computational efficiency in reconstructing building boundaries from airborne Lidar points. We proposed an adaptive convex hull algorithm, which is a modified version of local convex hull algorithm in three ways. The candidate points for boundary are first selected to improve efficiency depending on their local density. Second, a searching-space is adjusted adaptively, based on raw data structure, to extract boundary points more robustly. Third, distance between two points and their IDs are utilized in detecting the seed points of inner boundary to distinguish between inner yards and inner holes due to errors or occlusions. The practicability of the approach were evaluated on two urban areas where various buildings exist. The proposed method showed less shape-dissimilarity(8.5%) and proved to be two times more efficient than the other method.

Improved Rendering on Spherical Coordinate System using Convex Hull (컨벡스 헐을 이용한 개선된 구 좌표계 기반 렌더링 방법)

  • Kim, Nam-Jung;Hong, Hyun-Ki
    • Journal of Korea Game Society
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    • v.10 no.1
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    • pp.157-165
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    • 2010
  • This paper presents a novel real-time rendering algorithm based on spherical coordinate system of the object using convex hull. While OpenGL rendering pipeline touches all vertices of an object, the proposed method takes account the only visible vertices by examining the visible triangles of the object. In order to determine the visible areas of the object in its spherical coordinate representation, the proposed method uses 3D geometric relation of 6 plane equations of the camera frustum and the bounding sphere of the object. In addition, we compute the convex hull of the object and its maximum side factors for hidden surface removal. Simulation results showed that the quality of result image is almost same compared to original image and rendering performance is greatly improved.

Extraction and Modeling of Curved Building Boundaries from Airborne Lidar Data (항공라이다 데이터의 건물 곡선경계 추출 및 모델링)

  • Lee, Jeong Ho;Kim, Yong Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.4
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    • pp.117-125
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    • 2012
  • Although many studies have been conducted to extract buildings from airborne lidar data, most of them assume that all the boundaries of a building are straight line segments. This makes it difficult to model building boundaries containing curved segments correctly. This paper aims to model buildings containing curved segments as combination of straight lines and arcs. First, two sets of boundary points are extracted by adaptive convex hull algorithm and local convex hull algorithm with a larger radius. Then, arc segments are determined by average spacing of boundary points and intersection ratio of perpendicular lines. Finally, building boundary is modeled through regularization of least squares line or circle fitting. The experimental results showed that the proposed method can model the curved building boundaries as arc segments correctly by completeness of 69% and correctness of 100%. The approach will be utilized effectively to create automatically digital map that meets the conditions of the Korean digital mapping.

Feature Extraction of Asterias Amurensis by Using the Multi-Directional Linear Scanning and Convex Hull (다방향 선형 스캐닝과 컨벡스 헐을 이용한 아무르불가사리의 특징 추출)

  • Shin, Hyun-Deok;Jeon, Young-Cheol
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.3
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    • pp.99-107
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    • 2011
  • The feature extraction of asterias amurensis by using patterns is difficult to extract all the concave and convex features of asterias amurensis nor classify concave and convex. Concave and convex as important structural features of asterias amurensis are the features which should be found and the classification of concave and convex is also necessary for the recognition of asterias amurensis later. Accordingly, this study suggests the technique to extract the features of concave and convex, the main features of asterias amurensis. This technique classifies the concave and convex features by using the multi-directional linear scanning and form the candidate groups of the concave and convex feature points and decide the feature points of the candidate groups and apply convex hull algorithm to the extracted feature points. The suggested technique efficiently extracts the concave and convex features, the main features of asterias amurensis by dividing them. Accordingly, it is expected to contribute to the studies on the recognition of asterias amurensis in the future.

An Improved Convex Hull Algorithm Considering Sort in Plane Point Set (평면 점집합에서 정렬을 고려한 개선된 컨벡스 헐 알고리즘)

  • Park, Byeong-Ju;Lee, Jae-Heung;Kang, Byung-Ik
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.330-332
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    • 2012
  • 본 논문에서는 임의의 정렬되지 않은 평면 점집합(Plane Point Set)에서 정렬을 고려한 개선된 Convex Hull 알고리즘을 제안한다. 이 알고리즘은 Convex Hull의 극점(Extreme Point) 특성을 이용하여 처리 데이터를 한정하기 때문에 계산복잡도를 낮춘다. 각 단계마다 볼록 정점(Convex Vertex)만을 판별하는 조건을 이용하여 한 번의 스캔으로 온전한 Convex Set이 구한다. 알고리즘 초기에 점집합의 정렬이 필요한데, 이때 걸리는 시간이 알고리즘 전체 동작시간의 대부분을 차지하는 만큼, 특성에 맞는 방법을 사용하여 빠르게 정렬하였다. 일반적인 상황을 가정하고 점집합을 랜덤하게 구성하여 실험하였으며 기존의 알고리즘에 비해 약 두 배의 속도 향상이 있음을 확인하였다.

An Improved Convex Hull Algorithm Considering Sort in Plane Point Set (평면 점집합에서 정렬을 고려한 개선된 컨벡스 헐 알고리즘)

  • Park, Byeong-Ju;Lee, Jae-Heung
    • Journal of IKEEE
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    • v.17 no.1
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    • pp.29-35
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    • 2013
  • In this paper, we suggest an improved Convex Hull algorithm considering sort in plane point set. This algorithm has low computational complexity since processing data are reduced by characteristic of extreme points. Also it obtains a complete convex set with just one processing using an convex vertex discrimination criterion. Initially it requires sorting of point set. However we can't quickly sort because of its heavy operations. This problem was solved by replacing value and index. We measure the execution time of algorithms by generating a random set of points. The results of the experiment show that it is about 2 times faster than the existing algorithm.

Adjecent Object Segmentation Method Using Geometric Information in Cell Images (세포영상에서의 기하정보를 이용한 인접객체 분할 방법)

  • Eun, Sung-Jong;WhangBo, Taeg-Keun
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06b
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    • pp.296-299
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    • 2011
  • 임상 진단에서 환자의 의료 영상을 시각적으로 보고 해석하거나 또는 수작업으로 영상을 해석하여 진단에 이용한다. 이러한 수작업의 불편함을 해소하기 위하여 의료 영상처리 알고리즘들이 많이 연구되어오고 있다. 그 중 영상처리의 정확도 부분이 많은 문제가 되고 있는데, 특히 세포영상에서는 인접한 영역의 분할이 가장 중요시되고 있다. 본 논문은 이러한 인접영역의 분할을 위해 객체의 기하 정보인 곡률(Curvature) 정보와 컨벡스 헐(Convex Hull)을 통한 분할 방법을 제안하고자 한다. 실험 결과 87.5%의 정확도가 검출되었으며 향후 인접 객체의 내부정보까지 고려한 효과적인 분할 방법을 연구하고자 한다.

Incremental SVM for Online Product Review Spam Detection (온라인 제품 리뷰 스팸 판별을 위한 점증적 SVM)

  • Ji, Chengzhang;Zhang, Jinhong;Kang, Dae-Ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.89-93
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    • 2014
  • Reviews are very important for potential consumer' making choices. They are also used by manufacturers to find problems of their products and to collect competitors' business information. But someone write fake reviews to mislead readers to make wrong choices. Therefore detecting fake reviews is an important problem for the E-commerce sites. Support Vector Machines (SVMs) are very important text classification algorithms with excellent performance. In this paper, we propose a new incremental algorithm based on weight and the extension of Karush-Kuhn-Tucker(KKT) conditions and Convex Hull for online Review Spam Detection. Finally, we analyze its performance in theory.

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