• Title/Summary/Keyword: Point-to-Point

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Comparison and Evaluation of Classification Accuracy for Pinus koraiensis and Larix kaempferi based on LiDAR Platforms and Deep Learning Models (라이다 플랫폼과 딥러닝 모델에 따른 잣나무와 낙엽송의 분류정확도 비교 및 평가)

  • Yong-Kyu Lee;Sang-Jin Lee;Jung-Soo Lee
    • Journal of Korean Society of Forest Science
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    • v.112 no.2
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    • pp.195-208
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    • 2023
  • This study aimed to use three-dimensional point cloud data (PCD) obtained from Terrestrial Laser Scanning (TLS) and Mobile Laser Scanning (MLS) to evaluate a deep learning-based species classification model for two tree species: Pinus koraiensis and Larix kaempferi. Sixteen models were constructed based on the three conditions: LiDAR platform (TLS and MLS), down-sampling intensity (1024, 2048, 4096, 8192), and deep learning model (PointNet, PointNet++). According to the classification accuracy evaluation, the highest kappa coefficients were 93.7% for TLS and 96.9% for MLS when applied to PCD data from the PointNet++ model, with down-sampling intensities of 8192 and 2048, respectively. Furthermore, PointNet++ was consistently more accurate than PointNet in all scenarios sharing the same platform and down-sampling intensity. Misclassification occurred among individuals of different species with structurally similar characteristics, among individual trees that exhibited eccentric growth due to their location on slopes or around trails, and among some individual trees in which the crown was vertically divided during tree segmentation.

A Robust Power Transmission Lines Detection Method Based on Probabilistic Estimation of Vanishing Point (확률적인 소실점 추정 기법에 기반한 강인한 송전선 검출 방법)

  • Yoo, Ju Han;Kim, Dong Hwan;Lee, Seok;Park, Sung-Kee
    • The Journal of Korea Robotics Society
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    • v.10 no.1
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    • pp.9-15
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    • 2015
  • We present a robust power transmission lines detection method based on vanishing point estimation. Vanishing point estimation can be helpful to detect power transmission lines because parallel lines converge on the vanishing point in a projected 2D image. However, it is not easy to estimate the vanishing point correctly in an image with complex background. Thus, we first propose a vanishing point estimation method on power transmission lines by using a probabilistic voting procedure based on intersection points of line segments. In images obtained by our system, power transmission lines are located in a fan-shaped area centered on this estimated vanishing point, and therefore we select the line segments that converge to the estimated vanishing point as candidate line segments for power transmission lines only in this fan-shaped area. Finally, we detect the power transmission lines from these candidate line segments. Experimental results show that the proposed method is robust to noise and efficient to detect power transmission lines.

Comparison of Flooding Patterns according to the Location of the Collapse of Dam body (저수지 댐 붕괴 지점에 따른 침수 양상 비교)

  • Danxun, Liu;Lee, Gil-Ha
    • Journal of Environmental Science International
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    • v.31 no.6
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    • pp.461-470
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    • 2022
  • When an agricultural soil dam collapses, the extent of inundation and the rate of diffusion vary depending on where the collapse occurs in the dam body. In this study, a dam collapse scenario was established and a two-dimensional numerical model FLO-2D was used to closely examine the inundation pattern of the downstream residential area according to the dam collapse point. The results were presented as a flood risk map showing the changes and patterns of the extent of inundation spread. The flood level and the time to reach the maximum water level vary depending on the point of collapse, and the inundation of the downstream area proceeds rapidly in the order of the midpoint, left point, and right point collapse. In the left collapse point, the submergence appeared about 0.5 hour slower than the middle point, and the right collapse point appeared about 1 hour slower than the middle point. Since the relative damage pattern is different depending on the dam collapse point, insurance and disaster countermeasures will have to be established differently.

Convergence Point Adjustment Improving Visual Discomfort for a Zoom on a Stereoscopic Camera

  • Ha, Jong Soo;Kim, Dae Woong;Kim, Dong Hyun
    • Journal of the Optical Society of Korea
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    • v.20 no.5
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    • pp.633-640
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    • 2016
  • In a dual lens stereoscopic camera, a convergence point determines the stereopsis effects of a video. When a user zooms an object, a convergence point is fixed since it is not coupled with a zoom function. Due to the fixed convergence point, it is possible for a zoom to cause the excessive binocular disparity resulting in visual discomfort. In this paper, to solve this problem, we build the relational model including all phenomena possible to arise and propose the adjustment methods of a convergence point by the positions of a focus, an object and a convergence point. We also evaluate the experiments measuring a binocular disparity and the subjective test to investigate the visual comfort. The results show that one of the proposed methods produced more comfortable 3D images to viewers than the others.

Extraction of Geometric Primitives from Point Cloud Data

  • Kim, Sung-Il;Ahn, Sung-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2010-2014
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    • 2005
  • Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

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Change-point Approach for Analyzing Failure Trend in Repairable Generating Systems (수리 가능 발전기 시스템의 고장추세 분석을 위한 변화점 접근방법)

  • Hong, Min-Pyo;Bae, Suk-Joo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.1
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    • pp.11-19
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    • 2009
  • A number of trend test methods, i.e., Military Handbook test and Laplace test etc., have been applied to investigate recurrent failures trend in repairable systems. Existing methods provide information about only existence of trend in the system. In this paper, we propose a new change-point test based on the Schwarz Information Criterion(SIC). The change-point approach is more informative than other trend test methods in that it provides the number of change-points and the location of change-points if it exists, as well as the existence of change-point for recurrent failures. The change-point test is applied to nine 300MW generating units operated in East China. We confirm that the change-point test has a potential for establishing optimal preventive maintenance policy by detecting change-point of failure rate.

Generalization of Point Feature in Digital Map through Point Pattern Analysis (점패턴분석을 이용한 수치지형도의 점사상 일반화)

  • 유근배
    • Spatial Information Research
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    • v.6 no.1
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    • pp.11-23
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    • 1998
  • Map generalization functions to visualize the spatial data or to change their scale by changing the level of details of data. Until recently, the studies on map generalization have concentrated more on line features than on point features. However, point features are one of the essential components of digital maps and cannnot be ignored because of the great amount of information they carry. This study, therefore, aimed to find out a detailed procedure of point features' generalization. Particularly, this work chose the distribution pattern of point features as the most important factor in the point generalization in investigating the geometric characteristics of source data. First, it attempted to find out the characteristics of distribution pattern of point features through quadrat analysis with Grieg-Smith method and nearest-neighbour analysis. It then generalized point features through the generalization threshold which did not alter the characteristics of distribution pattern and the removal of redudant point feautres. Therefore, the generalization procedure of point features provided by this work maintained the geometric characteristics as much as possible.

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An Experimental Study of Moxa-Combustion Time by the Density of Moxa Material -On the point of time in the combustion stage- (애구(艾灸)의 연소(燃燒) 시간(時間)에 대한 실험적(實驗的) 연구(硏究) -구간별(區間別) 발현(發現) 시점(時點)을 중심(中心)으로-)

  • Park, Young-Bae;Kang, Sung-Keel;Koh, Hyung-Kyun;Oh, Hwan-Sup
    • The Journal of Korean Medicine
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    • v.15 no.2 s.28
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    • pp.241-252
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    • 1994
  • It is known that the pattern of combustion temperature can be classified into preheating, heating. retaining and cooling periods. In this experiment. the authors have studied the heating mechanism by the density of moxa material during the heating and retaining periods. The starting point. the point at which it begins to reach the maximum gradient temperature. the ending point of the heating period. and the ending point of the retaining period were measured in order to get effective stmulation by repetition of moxa-combustion. For the experiment. samples of 300mg. 400mg, and 500mg of moxa material were molded into conical molds with each 10mm in diameter and height resulting in the volume of $0.26cm^3$. The following results were obtained: The $300mg/0.26cm^3$ denstiy sample reached al1 points tested faster than the samples of $400mg/0.26cm^3$ and $500mg/0.26cm^3$ It dose not reveal any statistical differences between $400mg/0.26cm^3$ and $500mg/0.26cm^3$ in the ending point. the point at which it begins to reach the maximum gradient temperature of the heating period or the ending point of the reataining period The only difference shown was in the starting point of the heating period. According to the above results. it is concluded that the lower density moxa material reached each point of the the respective period faster than the high density moxa material.

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