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A Random Fusion of Mix 3D and Polar Mix to Improve Semantic Segmentation Performance in 3D Lidar Point Cloud 认领 引用
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作者 Bo Liu Li Feng Yufeng Chen 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期845-862,共18页
This paper focuses on the effective utilization of data augmentation techniques for 3Dlidar point clouds to enhance the performance of neural network models.These point clouds,which represent spatial information throu... This paper focuses on the effective utilization of data augmentation techniques for 3Dlidar point clouds to enhance the performance of neural network models.These point clouds,which represent spatial information through a collection of 3D coordinates,have found wide-ranging applications.Data augmentation has emerged as a potent solution to the challenges posed by limited labeled data and the need to enhance model generalization capabilities.Much of the existing research is devoted to crafting novel data augmentation methods specifically for 3D lidar point clouds.However,there has been a lack of focus on making the most of the numerous existing augmentation techniques.Addressing this deficiency,this research investigates the possibility of combining two fundamental data augmentation strategies.The paper introduces PolarMix andMix3D,two commonly employed augmentation techniques,and presents a new approach,named RandomFusion.Instead of using a fixed or predetermined combination of augmentation methods,RandomFusion randomly chooses one method from a pool of options for each instance or sample.This innovative data augmentation technique randomly augments each point in the point cloud with either PolarMix or Mix3D.The crux of this strategy is the random choice between PolarMix and Mix3Dfor the augmentation of each point within the point cloud data set.The results of the experiments conducted validate the efficacy of the RandomFusion strategy in enhancing the performance of neural network models for 3D lidar point cloud semantic segmentation tasks.This is achieved without compromising computational efficiency.By examining the potential of merging different augmentation techniques,the research contributes significantly to a more comprehensive understanding of how to utilize existing augmentation methods for 3D lidar point clouds.RandomFusion data augmentation technique offers a simple yet effective method to leverage the diversity of augmentation techniques and boost the robustness of models.The insights gained from this research can pave the way for future work aimed at developing more advanced and efficient data augmentation strategies for 3D lidar point cloud analysis. 展开更多
关键词 3D lidar point cloud data augmentation RandomFusion semantic segmentation
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A century of tunnel-landslide interaction:Anatomy of T7 Tunnel,Nurhak-Gölbaşı(Türkiye) 认领 引用
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作者 KARAHAN Servet POSLUK Evren +1 位作者 BUYUKDEMIRCI F.Burak GOKCEOGLU Candan 《Journal of Mountain Science》 SCIE CSCD 2026年第5期1884-1906,共23页
The T7 Tunnel,a single-track railway tunnel constructed in 1933 on the Diyarbakır-Fevzipaşa line in southeastern Türkiye,has experienced progressive damage due to tunnellandslide interaction for nearly a century.... The T7 Tunnel,a single-track railway tunnel constructed in 1933 on the Diyarbakır-Fevzipaşa line in southeastern Türkiye,has experienced progressive damage due to tunnellandslide interaction for nearly a century.Primarily used for freight transport,the tunnel underwent various temporary interventions to maintain traffic until the damage became critical following the 6 February 2023 Türkiye Earthquake.This study investigates the causes and extent of deterioration and proposes a permanent engineering solution.A comprehensive characterization was conducted using historical records,field observations,drilling data,insitu and laboratory tests,and Light Detection and Ranging(LiDAR)measurements.The investigation revealed a 220 m wide,630 m long landslide with multiple fracture surfaces enveloping the tunnel.LiDAR data showed cumulative tunnel displacements of up to 250 cm,corresponding to an average movement rate of 2.7 cm/year since construction.Based on landslide analysis,the optimal engineering decision was to relocate the tunnel alignment 130 m deeper into stable bedrock.The new tunnel was constructed and completed without incident on May 30,2025.Post-construction monitoring confirms no deformation inside or outside the tunnel,indicating that the century-long engineering challenges have been permanently resolved.The methodology and engineering approaches presented provide a valuable reference for managing tunnel-landslide hazards in mountainous terrains. 展开更多
关键词 Tunnel Landslide Railway Earthquake LiDAR point cloud Damage
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Estimating underground mine ventilation friction factors from low density 3D data acquired by a moving LiDAR 认领 引用 被引量：10
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作者 Curtis Watson Joshua Marshall 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2018年第4期650-655,共6页
Ventilation system analysis for underground mines has remained mostly unchanged since the Atkinson method was made popular by Mc Elroy in 1935. Data available to ventilation technicians and engineers is typically limi... Ventilation system analysis for underground mines has remained mostly unchanged since the Atkinson method was made popular by Mc Elroy in 1935. Data available to ventilation technicians and engineers is typically limited to the quantity of air moving through any given heading. Because computer-aided modelling, simulation, and ventilation system design tools have improved, it is now important to ensure that developed models have the most accurate information possible. This paper presents a new technique for estimating underground drift friction factors that works by processing 3 D point cloud data obtained by using a mobile Li DAR. Presented are field results that compare the proposed approach with previously published algorithms, as well as with manually acquired measurements. 展开更多
关键词 Mine ventilation Mine design Mobile mapping Roughness estimation Friction factors LiDAR3D point clouds
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海量点云的边缘快速提取算法 认领 引用 被引量：32
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作者 王宗跃 马洪超 +1 位作者 徐宏根 杨志伟 《计算机工程与应用》 北大核心 2010年第36期213-215,共3页
提出一种海量点云边缘快速提取算法。该算法先对点云数据进行格网组织,然后排除非边缘的离散点,最后采用AlphaShapes判断条件提取边缘。该算法牺牲少量格网数据组织时间,节约大量的Alpha Shapes条件判断时间,从而显著提高算法效率。在V... 提出一种海量点云边缘快速提取算法。该算法先对点云数据进行格网组织,然后排除非边缘的离散点,最后采用AlphaShapes判断条件提取边缘。该算法牺牲少量格网数据组织时间,节约大量的Alpha Shapes条件判断时间,从而显著提高算法效率。在VC环境下实现了该算法,实验结果表明该算法不仅具有提取外边界、空洞等功能,而且效率高。 展开更多
关键词 机载激光雷达 点云 边缘
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Identification of global main cable line shape parameters of suspension bridges based on local 3D point cloud 认领 引用 被引量：1
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作者 Yurui Li Danhui Dan Ruiyang Pan 《Low-carbon Materials and Green Construction》 2025年第1期1-12,共12页
Main cable line shape measurement and parameter identification are a critical task in the construction monitoring and service maintenance of suspension bridges.3D LiDAR scanning can simultaneously obtain the coordinat... Main cable line shape measurement and parameter identification are a critical task in the construction monitoring and service maintenance of suspension bridges.3D LiDAR scanning can simultaneously obtain the coordinates of multiple points on the target,offering high accuracy and efficiency.As a result,it is expected to be used in applications requiring rapid,large-scale measurements,such as main cable line shape measurement for suspension bridges.However,due to the large span and tall main towers of suspension bridges,the LiDAR field of view often encounters obstructions,making it difficult to obtain high-quality point clouds for the entire bridge.The collected point clouds are typically unevenly distributed and of poor quality.Therefore,LiDAR is used to monitor the local cable line shape.This paper proposes an innovative non-uniform sampling method that adjusts the sampling density based on the main cable’s rate of change.Additionally,the Random Sample Consensus(RANSAC)algorithm,the ordinary least squares,and center-of-mass calibration are applied to identify and optimize the geometric parameters of the cross-section point cloud of the main cable.Given the strong design prior information available during suspension bridge construction,Bayesian theory is applied to predict and adjust the global line shape of the main cable.The study shows that using LiDAR for cable point cloud measurement enables rapid acquisition of high-precision point cloud data,significantly enhancing data collection efficiency.The method proposed in this paper offers advantages such as highly automated,low risk,low cost,and sustainability,making it suitable for green monitoring throughout the entire main cable construction process. 展开更多
关键词 Suspension Bridge Main Cable Line Shape Parameter Identification LiDAR Point Cloud Bayesian Theory
3D Vehicle Detection Based on LiDAR and Camera Fusion 认领 引用 被引量：3
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作者 Yingfeng Cai Tiantian Zhang +3 位作者 Hai Wang Yicheng Li Qingchao Liu Xiaobo Chen 《Automotive Innovation》 EI CSCD 2019年第4期276-283,共8页
Nowadays,the deep learning for object detection has become more popular and is widely adopted in many fields.This paper focuses on the research of LiDAR and camera sensor fusion technology for vehicle detection to ens... Nowadays,the deep learning for object detection has become more popular and is widely adopted in many fields.This paper focuses on the research of LiDAR and camera sensor fusion technology for vehicle detection to ensure extremely high detection accuracy.The proposed network architecture takes full advantage of the deep information of both the LiDAR point cloud and RGB image in object detection.First,the LiDAR point cloud and RGB image are fed into the system.Then a high-resolution feature map is used to generate a reliable 3D object proposal for both the LiDAR point cloud and RGB image.Finally,3D box regression is performed to predict the extent and orientation of vehicles in 3D space.Experiments on the challenging KITTI benchmark show that the proposed approach obtains ideal detection results and the detection time of each frame is about 0.12 s.This approach could establish a basis for further research in autonomous vehicles. 展开更多
关键词 Vehicle detection LiDAR point cloud RGB image Fusion
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