• 한국컴퓨터그래픽스학회논문지
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• 제18권3호
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• pp.1-7
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• 2012

본 논문에서는 단백질 분자 간의 인터페이스를 계산하는 알고리즘을 제안한다. 분자가 반데르바스 (van der Waals) 반경을 갖는 구의 집합으로 표현될 때, 공간 상의 한 점 p로부터 분자까지의 거리는 p로부터 가장 가까운 구까지의 거리에 대응한다. 분자 인터페이스는 두 개의 분자에 대해 같은 거리에 있는 점들로 구성된다. 제안된 알고리즘은 공간을 복셀의 집합로 분할한뒤, 각 복셀을 지나는 구의 위치 정보를 저장하여 복셀맵 (voxel map)을 구성하였다. 복셀맵을 이용하여 한 점으로부터 분자까지의 거리를 계산하며, GPU (graphic processor unit)를 이용하여 병렬처리를 수행함으로써 효율적으로 인터페이스를 근사한다.

• ETRI Journal
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• 제44권1호
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• pp.51-61
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• 2022

In this paper, we introduced a novel voxel-wise UV parameterization and view-dependent texture synthesis for the immersive rendering of a truncated signed distance field (TSDF) scene model. The proposed UV parameterization delegates a precomputed UV map to each voxel using the UV map lookup table and consequently, enabling efficient and high-quality texture mapping without a complex process. By leveraging the convenient UV parameterization, our view-dependent texture synthesis method extracts a set of local texture maps for each voxel from the multiview color images and separates them into a single view-independent diffuse map and a set of weight coefficients for an orthogonal specular map basis. Furthermore, the view-dependent specular maps for an arbitrary view are estimated by combining the specular weights of each source view using the location of the arbitrary and source viewpoints to generate the view-dependent textures for arbitrary views. The experimental results demonstrate that the proposed method effectively synthesizes texture for an arbitrary view, thereby enabling the visualization of view-dependent effects, such as specularity and mirror reflection.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.436-443
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• 2011

Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.423-427
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• 1993

An efficient 3-axis NC milling simulator is presented. The geometric simulation of milling is based on z-map structure and voxels. For the graphic simulation,dimetric projection is adopted. As a result, two faces of a voxel are exposed and they are overlapped. Visible faces are determined by using z-butter method. The simulation system is developed in IBM-PC compatible with satisfactory result.

• 한국멀티미디어학회논문지
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• 제15권6호
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• pp.794-804
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• 2012

단백질 분자에 대해 공간 상의 한 점으로부터의 최소 거리를 계산하거나, 임의의 점에 대한 충돌을 감지하는 등의 proximity query는 분자에 대한 기하학적 연산을 수행하기 위해 매우 중요한 기본 연산이다. Proximity query의 계산 시간 효율성은 분자가 어떤 자료구조로 표현되는가에 따라 크게 달라질 수 있다. 본 논문에서는 GPU 가속을 이용하여 효율적으로 proximity 연산을 수행하기 위한 기법을 제안하고자 한다. 분자에 대응하는 구의 집합에 대해 복셀 맵 (voxel map)과 스피어 트리 (sphere tree) 를 사용한 자료구조를 제안하며 각 자료구조에 대응되는 알고리즘을 제시한다. 또한, 1,000개~15,000개의 원자를 포함하는 분자에 대한 실험을 통해 두 자료구조의 성능이 기존 자료구조에 비해 최소 3배에서 최대 633배 향상되었음을 보인다.

• 정보처리학회논문지A
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• 제19A권2호
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• pp.73-76
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• 2012

본 논문에서는 단백질 분자로부터 표면 원자를 효율적으로 발견하는 알고리즘을 제안한다. 표면 원자란, 주어진 probe solvent $P$가 단백질 분자와 충돌하지 않고 접한다고 가정할 때, $P$와 접할 수 있는 원자의 집합을 의미한다. 단백질 분자를 구성하는 원자들은 반데르바스 반경을 갖는 구의 집합으로 표현되며, probe solvent 역시 구로 대응된다. $P$의 반경에 대해 분자의 오프셋 곡면을 구하여 표면 원자를 발견하는 알고리즘을 제안한다. 제안된 알고리즘은 각 구의 오프셋 곡면에 대해 복셀 맵(voxel map)을 구성하여 효율적으로 분자의 오프셋 곡면을 구하며, GPU (graphic processor unit)를 활용한 병렬처리를 수행하여 최대 6,412개의 원자를 갖는 분자에 대해 42.87 millisecond 내에 표면 원자를 발견한다.

• 한국BIM학회 논문집
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• 제10권4호
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• pp.32-39
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• 2020

In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.

• International Journal of Advanced Culture Technology
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• 제9권4호
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• pp.302-306
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• 2021

Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권1호
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• pp.1-6
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• 2014

현재까지 컨벡스헐 (convex hull) 의 계산 알고리즘들은 주로 점 집합 (point set) 에 대해 연구가 수행되어 왔다. 본 논문에서는 이산 공간에서 다양한 반경을 갖는 구 집합에 대한 컨벡스헐을 근사하는 방법을 제시한다. 구 집합에 대한 컨벡스헐 계산은, 특히 단백질 분자의 구조적인 특성을 연구하는 여러 응용분야에서 계산 효율성을 증대시키기 위한 기반 기술이라 할 수 있다. 분자에 대응하는 구의 집합에 대해 복셀 맵 (voxel map) 자료구조를 적용하고 이를 이용하여 컨벡스헐을 계산하는 알고리즘을 제시한다. 제안된 방법은 GPU를 활용한 병렬처리를 수행하여 평균적으로 6,400개 이하의 구가 포함된 집합에 대해 40ms 이내에 컨벡스헐을 계산하는 성능을 보인다.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.996-1002
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• 2015

In this paper, we present an effective system for the 3D scene labeling of objects from RGB-D videos. Our system uses a Markov Random Field (MRF) over a voxel representation of the 3D scene. In order to estimate the correct label of each voxel, the probabilistic graphical model integrates both scores from sliding window-based object detectors and also from object location prior maps. Both the object detectors and the location prior maps are pre-trained from manually labeled RGB-D images. Additionally, the model integrates the scores from considering the geometric constraints between adjacent voxels in the label estimation. We show excellent experimental results for the RGB-D Scenes Dataset built by the University of Washington, in which each indoor scene contains tabletop objects.