• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.47-48
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• 2021

본 논문에서는 대용량의 3D 데이터 시퀀스의 압축을 진행한다. 3D 데이터 시퀀스의 각 프레임에서 Pose Estimation을 통해 3D Skeleton을 추출한 뒤, 포인트 클라우드를 skeleton에 묶는 리깅 과정을 거치고, 다음 프레임과 같은 자세로 deformation을 진행한다. 다음 프레임과 같은 자세로 변형된 포인트 클라우드와 실제 다음 프레임의 포인트 클라우드를 비교하여, 두 데이터에 모두 있는 점, 실제 다음 프레임에만 있는 점, deformation한 데이터에만 있는 점으로 분류한다. 두 데이터에 모두 있는 점을 제외하고 나머지 두 분류의 점들을 저장함으로써 3D 시퀀스 데이터를 압축할 수 있다.

• Korean Journal of Computational Design and Engineering
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• v.15 no.1
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• pp.33-42
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• 2010

In this study, new medial surface calculation methods using Voronoi diagrams are investigated for the point samples extracted on closed surface models. The medial surface is defined by the closure of all points having more than one closest point on the shape boundary. It is a one of essential geometric information in 3D and can be used in many areas such as 3D shape analysis, dimension reduction, freeform shape deformation, image processing, computer vision, FEM analysis, etc. In industrial parts, the idealized solid parts and shell shapes including sharp edges and vertices are frequently used. Other medial surface extraction methods using Voronoi diagram have inherent separation and branch problems, so that they are not appropriate to the sharp edged objects and have difficulties to be applied to industrial parts. In addition, the branched surfaces on sharp edges in shell shapes should be eliminated to obtain representative medial shapes. In order to avoid separation and branch problems, the new approach by analyzing the shapes and specially sampling on surfaces has been developed.

• Journal of the Korea Computer Graphics Society
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• v.7 no.1
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• pp.1-9
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• 2001

We present a scheme and a data structure that decompose the space into adaptive-sized cells to improve the visualization of soft objects. Soft objects are visualized through the evaluation of the field functions at every point of the space. According to the propsed scheme, the affecting soft objects for a point in the space is searched through the data structure called interval tree based on the bounding volume of the components, which represent a soft object whose defining primitive(skeleton) is a simple geometric object such as point or line segment. The bounding volume of each component is generated with respect to the radius of a local field function of the component, threshold value, and the relations between the components and other neighboring components. The proposed scheme can be used in many applications for soft objects such as modeling and rendering, especially in interactive modeling process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1199-1206
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• 2015

This paper introduces an algorithm for computing similarity between two poses in the motion capture data with different scale of skeleton, different number of joints and different joint names. The proposed algorithm first performs the topological analysis on the skeleton hierarchy for classifying the joints into more meaningful groups. The global joints positions of each joint group then are aggregated into a point cloud. The number of joints and their positions are automatically adjusted in this process. Once we have two point clouds, the algorithm finds an optimal 2D transform matrix that transforms one point cloud to the other as closely as possible. Then, the similarity can be obtained by summing up all distance values between two points clouds after applying the 2D transform matrix. After some experiment, we found that the proposed algorithm is able to compute the similarity between two poses regardless of their scale, joint name and the number of joints.

• ETRI Journal
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• v.39 no.2
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• pp.181-190
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• 2017

The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.58.1-58.1
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• 2013

The main idea of the Alcock-Paczynski (AP) test is that, if we use a wrong distance-redshift relation to infer the shape of a spherical object in the Universe, this object may look non-spherical. To probe the cosmic expansion history through the AP test, the key point is to find something which is known as spherical in the Universe. We propose two possible ways applying the AP test to the large scale structure (LSS): 1) Based on the observed galaxies or quasars, one built up the beta-skeleton tracing the LSS, and investigating the inhomogeneity of the connections; 2) One reconstructs the smoothed density-contrast gradient field based on LSS observations, and investigating the inhomogeneity of the gradient vectors. Compared with some existed methods probing AP effect through 2-point correlation function, galaxy pairs, or voids, our methods have various advantages: 1) The information of both the high and low dense regions of the LSS are taken into account. 2) The redshift space distortion as the main contamination to the AP effect can be easily removed.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.4
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• pp.562-573
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• 1997

Comparative osteology of Chromis notata, C. analis and C. fumea was studied based on the samples collected from the Korean waters. The three species are distinguished by the shape of cranium, visceral skeleton, vertebra and caudal skeleton. Chromis notata has a glossohyal which is slightly curved in shape while two other species are deeply curved. C. analis has three spiniform procurrent caudal rays while others have two. C. fumes could be distinguished easily by the shape of preopercle which is serrate in posterior margin. This investigator reveals following bones as new taxonomic criteria for the genus Chromis in Korea. In cranium, height of supraoccipital, height of process of parasphenoid and anterior margin of basisphenoid, in visceral skeleton, presence of fine papilla-like process at the surface of preopercular sensory canal, in orbital bone, width of preorbital, in hyoid arch, shape of glossohyal, union state between lower hypohyal and ceratohyal and union state between ceratohyal and epihyal, in shoulder girdle bone, dorsal margin of posttemporal, width of upper postclavicle, posterior end of lower postclavicle and posterior margin of first actinost bone, in vertebrae, beginning point of parapophysis, in caudal skeleton, upper shape of second neural spine of pleural centrum.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.14-23
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• 2016

The problem of fitting B-spline curves to planar point clouds is studied in this paper. A novel method is proposed to deal with the most challenging case where multiple intersecting curves or curves with self-intersection are necessary for shape representation. A method based on Delauney Triangulation of data points is developed to identify connected components which is also capable of removing outliers. A skeleton representation is utilized to represent the topological structure which is further used to create a weighted graph for deciding the merging of curve segments. Different to existing approaches which utilize local shape information near intersections, our method considers shape characteristics of curve segments in a larger scope and is thus capable of giving more satisfactory results. By fitting each group of data points with a B-spline curve, we solve the problems of curve structure reconstruction from point clouds, as well as the vectorization of simple line drawing images by drawing lines reconstruction.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.866-870
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• 1995

To make a mobile robot to get to a goal point, path which connects the mobile robot and the goal point is needed and a path planning is necessary. There are various kinds of a path planning. Well known methods are skeleton method, cell decomposition method and potential field method. But each method has both fortes and defects. In this paper, we propose a new method of path planning to find a path for mobile robot. It is obtained by modifying a Voronoi diagram. An original Voronoi diagram can make a safe path but its result is not satisfied. First defect of path, finded by the original Voronoi diagram, is sulplus of safty which make a path longer. Second defect is that the original Voronoi diagram method has a problem of connecting the Voronoi daigram with start/goal point of mobile robot. These defects are removed in proposed algorithm in this paper. We define a function to show the quality of paths. And by computer simulation, paths are compared and its result are shown.

• Journal of KIBIM
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• v.9 no.4
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• pp.31-40
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• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.