• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1211-1212
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• 2022

본 논문에서는 증강현실(AR)과 가상현실(VR)에서 가상 3D 컨텐츠의 고화질 영상을 처리할 수 있는 컨텐츠의 자료 형인 포인트 클라우드(point cloud)에 대하여 알아보고, 포인트 클라우드 데이터의 특징에 대하여 논한다. 이후 증강현실과 가상현실에서 포인트 클라우드를 효율적으로 사용하기 위하여 포인트 클라우드의 재가공 (Preprocess)를 통하여 효율적으로 포인트 클라우드 3D 컨텐츠를 사용할 수 있는 알고리즘을 제안한다.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.457-461
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• 2013

This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.79-87
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• 2016

As 3D geospatial information is demanded, terrestrial laser scanners which can obtain 3D model of objects have been applied in various fields such as Building Information Modeling (BIM), structural analysis, and disaster management. To acquire precise data, performance evaluation of a terrestrial laser scanner must be conducted. While existing 3D surveying equipment like a total station has a standard method for performance evaluation, a terrestrial laser scanner evaluation technique for users is not established. This paper categorizes and analyzes error sources which generally occur in terrestrial laser scanning. In addition to the prior researches about categorizing error sources of terrestrial Laser scanning, this paper evaluates the error sources by the actual field tests for the smooth in-situ applications.The error factors in terrestrial laser scanning are categorized into interior error caused by mechanical errors in a terrestrial laser scanner and exterior errors affected by scanning geometry and target property. Each error sources were evaluated by simulation and actual experiments. The 3D coordinates of observed target can be distortedby the biases in distance and rotation measurement in scanning system. In particular, the exterior factors caused significant geometric errors in observed point cloud. The noise points can be generated by steep incidence angle, mixed-pixel and crosstalk. In using terrestrial laser scanner, elaborate scanning plan and proper post processing are required to obtain valid and accurate 3D spatial information.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.8
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• pp.251-260
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• 2014

3D point data is utilized in various industry domains for its high accuracy to the surface information of an object. It is substantially utilized in geography for terrain scanning and analysis. Generally, 3D point data need to be changed by Gridding which produces a regularly spaced array of z values from irregularly spaced xyz data. But it requires long processing time and high resource cost to interpolate grid coordination. Kriging interpolation in Gridding has attracted because Kriging interpolation has more accuracy than other methods. However it haven't been used frequently since a processing is complex and slow. In this paper, we presented a parallel Gridding algorithm which contains Kriging and an application of grid data structure to fit MapReduce paradigm to this algorithm. Experiment was conducted for 1.6 and 4.3 billions of points from Airborne LiDAR files using our proposed MapReduce structure and the results show that the total execution time is decreased more than three times to the convention sequential program on three heterogenous clusters.

• 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.

• Advances in Computational Design
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• v.3 no.4
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• pp.319-338
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• 2018

High-performing architecture should be designed by taking into account the mutual dependency between the new building and the local context. The performative architecture plays an important role to avert any unforeseen failures after the building has been built; particularly ones related to the microclimate impacts that affect the human comfort. The use of the concept of solar envelopes helps designers to construct the developable mass of the building design considering the solar access and the site obstruction. However, the current analysis method using solar envelopes lack in terms of integrating the detailed information of the existing context during the simulation process. In architectural design, often the current site modelling not only absent in preserving the complex geometry but also information on the surface characteristics. Currently, the emerging applications of point clouds offer a great possibility to overcome these limitations, since they include the attribute information such as XYZ as the position information and RGB as the color information. This study particularly presents a comparative analysis between the manually built 3D models and the models generated from the point cloud data. The modelling comparisons focus on the relevant factors of solar radiation and a set of simulation to calculate the performance indicators regarding selected portions of the models. The experimental results emphasize an introduction of the design approach and the dataset visibility of the 3D existing environments. This paper ultimately aims at improving the current architectural decision of support environment means, by increasing the correspondence between the digital models for performance analysis and the real environments (context of design) during the conceptual design phase.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.83-85
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• 2017

We conducted an unbiased near- to mid-infrared imaging and spectroscopic survey of the Large Magellanic Cloud (LMC) as a part of the AKARI Mission Program "Large-area Survey of the LMC" (LSLMC, PI: T. Onaka). An area of about 10 square degrees of the LMC was observed by five photometric bands (3.2, 7, 11, 15, and $24{\mu}m$) and a low-resolution slitless prism ($2-5{\mu}m$, R ~20) equipped with AKARI /IRC. We constructed and publicly released photometric and spectroscopic catalogues of point sources in the LMC based on the survey data. The catalogues provide a large number of near-infrared spectral data, coupled with complementary broadband photometric data. Combined use of the present AKARI LSLMC catalogues with other infrared point source catalogues of the LMC possesses scientific potential that can be applied to various astronomical studies.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.17-23
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• 2016

This paper presents the implementation of altitude and attitude measurement algorithm using stereo camera for an unmanned aerial vehicle (UAV). Depth images are generated by calibrating the stereo cameras, and converted into 3D point cloud data. By applying a plane fitting algorithm to the resultant point cloud, altitude from ground level, and roll and pitch angles are extracted. To verify the performance, experimental results are provided by comparing with those of the motion caption system.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.269-279
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• 2020

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2414-2433
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• 2019

The aim of this paper is to design a 3D laser radar prototype based on laser triangulation. The mathematical model of distance sensitivity is deduced; a pixel-distance conversion formula is discussed and used to complete 3D scanning. The center position extraction algorithm of the spot is proposed, and the error of the linear laser, camera distortion and installation are corrected by using the proposed weighted average algorithm. Finally, the three-dimensional analytic computational algorithm is given to transform the measured distance into point cloud data. The experimental results show that this 3D laser radar can accomplish the 3D object scanning and the environment 3D reconstruction task. In addition, the experiment result proves that the product of the camera focal length and the baseline length is the key factor to influence measurement accuracy.