Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs,this study presents an intelligent strategy for extracting road cracks.This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images.The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously.A convolutional neural network is utilized to extract cracks from the panoramic sequence image.The extracted sequence image is then aligned with the laser point cloud,enabling the assignment of RGB information to the vehicle-mounted three dimensional(3D)point cloud and location information to the two dimensional(2D)panoramic image.Additionally,a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud.The three-dimensional data pertaining to the cracks can be acquired.The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks.The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks.This approach exhibits superior accuracy when compared to conventional methods.Moreover,it facilitates rapid and accurate identification and localization of road cracks,thereby playing a crucial role in ensuring road maintenance and traffic safety.Consequently,this technique finds extensive application in the domains of intelligent transportation and urbanization development.The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

Landslide data mosaicking based on an airborne laser point cloud and multi-beam sonar images

Landslides are one of the most disastrous geological hazards in southwestern China.Once a landslide becomes unstable,it threatens the lives and safety of local residents.However,empirical studies on landslides have predominantly focused on landslides that occur on land.To this end,we aim to investigate ashore and underwater landslide data synchronously.This study proposes an optimized mosaicking method for ashore and underwater landslide data.This method fuses an airborne laser point cloud with multi-beam depth sounder images.Owing to their relatively high efficiency and large coverage area,airborne laser measurement systems are suitable for emergency investigations of landslides.Based on the airborne laser point cloud,the traversal of the point with the lowest elevation value in the point set can be used to perform rapid extraction of the crude channel boundaries.Further meticulous extraction of the channel boundaries is then implemented using the probability mean value optimization method.In addition,synthesis of the integrated ashore and underwater landslide data angle is realized using the spatial guide line between the channel boundaries and the underwater multibeam sonar images.A landslide located on the right bank of the middle reaches of the Yalong River is selected as a case study to demonstrate that the proposed method has higher precision thantraditional methods.The experimental results show that the mosaicking method in this study can meet the basic needs of landslide modeling and provide a basis for qualitative and quantitative analysis and stability prediction of landslides.

Pedestrian detection algorithm based on video sequences and laser point cloud

Pedestrian detection is a critical problem in the field of computer vision. Although most existing algorithms are able to detect pedestrians well in controlled environ- ments, it is often difficult to achieve accurate pedestrian de- tection from video sequences alone, especially in pedestrian- intensive scenes wherein pedestrians may cause mutual oc- clusion and thus incomplete detection. To surmount these dif- ficulties, this paper presents pedestrian detection algorithm based on video sequences and laser point cloud. First, laser point cloud is interpreted and classified to separate pedes- trian data and vehicle data. Then a fusion of video image data and laser point cloud data is achieved by calibration. The re- gion of interest after fusion is determined using feature in- formation contained in video image and three-dimensional information of laser point cloud to remove false detection of pedestrian and thus to achieve pedestrian detection in inten- sive scenes. Experimental verification and analysis in video sequences demonstrate that fusion of two data improves the performance of pedestrian detection and has better detection results.

Decoupling of the position and angular errors in laser pointing with a neural network method

In laser-pointing-related applications,when only the centroid of a laser spot is considered,then the position and angular errors of the laser beam are often coupled together.In this study,the decoupling of the position and angular errors is achieved from one single spot image by utilizing a neural network technique.In particular,the successful application of the neural network technique relies on novel experimental procedures,including using an appropriate small-focal-length lens and tilting the detector,to physically enlarge the contrast of different spots.This technique,with the corresponding new system design,may prove to be instructive in the future design of laser-pointing-related systems.

基于PointNet++进行附属设施语义分割的隧道收敛变形分析

随着城市轨道交通日趋广泛,隧道结构变形引起的地铁安全事故凸显,亟需对运营期隧道进行变形检测。隧道衬砌作为隧道变形分析的研究对象,衬砌内表面存在的大量附属设施影响隧道收敛变形分析精度。为了提高变形分析精度,解决点云处理环节中存在的自动化程度低的问题,提出基于PointNet++点云语义分割的隧道收敛变形分析方法。首先利用深度学习方法进行点云语义分割,对隧道衬砌附属设施进行自动滤除。然后对隧道衬砌进行断面提取,利用随机抽样一致性算法(Random Sample Consensus,RANSAC)对隧道断面点云进行采样,分析隧道收敛变形程度,从Z+F PROFILER 9012A激光断面扫描仪获取山东省济南市地铁盾构隧道点云实测数据上并进行应用。研究结果表明:所提出的处理方法可以有效地将大规模隧道衬砌与连接紧密的附属设施分离出来,隧道附属设施总体分类精度达到96%,滤波结果较好地保留了隧道衬砌原始形态特征。在对隧道整体和局部收敛变形分析的重复性验证中,测试区间内隧道整体变形精度往返测长半轴平均偏差为1.04 mm,短半轴平均偏差为0.9 mm,测试区间内隧道局部收敛变形往返测标准差最小为0.773 mm,最大为0.938 mm,可以满足隧道收敛变形分析的精度需求。研究结果可以有效提升处理大规模隧道数据的自动化程度,具有良好的有效性与可靠性,对运营期地铁隧道收敛变形检测或监测有较好的实践应用意义。

基于知识蒸馏和定位引导的Pointpillars点云检测网络

激光雷达数据由于其几何特性,被广泛应用于三维目标检测任务中。由于点云数据的稀疏性和不规则性,难以实现特征提取的质量和推理速度间的平衡。本文提出一种基于体柱特征编码的三维目标检测算法,以Pointpillars网络为基础,设计Teacher-Student模型框架对回归框尺度进行蒸馏,增加蒸馏损失,优化训练网络模型,提升特征提取的质量。为进一步提高模型检测效果,设计定位引导分类项,增加分类预测和回归预测之间的相关性,提高物体识别准确率。本网络所做改进没有引入额外的网络嵌入。算法在KITTI数据集上的实验结果表明,相比于基准网络,在三维模式下的平均精度值从60.65%提升到了64.69%,鸟瞰图模式下的平均精度值从67.74%提升到70.24%。模型推理速度为45 FPS,在提升检测精度的同时满足了实时性要求。

TREATMENT OF BRONCHIAL ASTHMA WITH CO_2 LASER IRRADIATING POINTS

Therapeutic effect of bronchisl asthma treated With CO2 laser irradiating points was ob-served.Ninety-six cases of bronchial asthma,that were considered cold and insufficiency type accord-ing to TCM,were divided into two groups:one treated with CO2 laser irradiation at Tiantu（CV 22）,Danzhong（CV 17）,Feishu（BL13）and Dingchuan（EX-BI）（n=48）,and the other with warmmoxibustion at same points（n=48）.The symptoms,physical signs and pulmonary ventilation（PEF.VC,FEV1.0,FEV1％and MMEF）were taken as parameter.xhe results showed that thetherapeutic effect In laser irradiation group was better than that in moxibustion group.Moreover,laser irradiation could obviously improve pulmonary ventilation in patients.Therefore,CO2 laser irra-diation is an effective therapy for bronchial asthma.

Laser therapy on points of acupuncture on nerve repair

Paresthesia is the name given to a temporary or permanent sensory loss caused by several surgical procedures that affected the peripheral sensory nerve.In dentistry,common iatrogenic procedures that can lead to sensory loss include third molar removal,

THE TREATMENT OF CERVICAL SPONDYLOPATHY BY LASER ACUPUNCTURE AT THE CERVICAL JIAJI POINTS: AN ANALYSIS OF THERAPEUTIC EFFECT OF 102 CASES

Laser acupuncture therapy was employed in the treatment of spondylopathy.Thetherapeutic effect of the three types of the spondylopathy,nerve root type,vertebral artery type andspinal cord type were stuied and compared.The results indicate a significant difference between thethree types of spondylopathy.The best therapeutic effect was obtained in nerve root type with a remarkable effective rate of 98.5％;the effective rates for the vertebral artery type and the spinal cordtype were 92.3％and 25％,respectively.Combining laser irradiatlon with acupuncture,the therapyposseses the functions of acupuncture,heat effect and mild moxibustion action.Therefore,it showedeffect quickly and had the advantages of short treatment course and high therapeutic effect.Clinicalobservation has confirmed that laser acupuncture is more effective than single laser irradiation.Thistherapy offers another simple but effective method for the treatment of spondylopathy.

基于改进PointPillars的点云车辆目标检测

针对自动驾驶领域中,激光雷达获取的点云数据存在稀疏性以及边缘噪点误检等问题,提出一种基于改进PointPil-lars的点云车辆目标检测方法。首先,基于SimAM注意力机制改进体素化特征输入,使得网络特征提取阶段能更加关注关键信息,提高特征学习的全局性。其次,基于卷积块注意力模块(CBAM)改进骨干网络结构,提出全新的轻量化通道注意力模块Tiny-CAM和可变形空间注意力模块Deformable-SAM,构建Multi-CBAM骨干网络,提升网络特征提取及特征融合能力。在KITTI数据集以及非公开车库点云数据集上进行验证,实验结果表明,与原网络相比,改进PointPillars方法具有更高的检测精度,平均检测精度提升2.98%,针对遮挡小于30%的点云车辆目标检测精度提升6.51%,证明了该方法的有效性。

Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.

Pre-process algorithm for satellite laser ranging data based on curve recognition from points cloud

The satellite laser ranging （SLR） data quality from the COMPASS was analyzed, and the difference between curve recognition in computer vision and pre-process of SLR data finally proposed a new algorithm for SLR was discussed data based on curve recognition from points cloud is proposed. The results obtained by the new algorithm are 85 % （or even higher） consistent with that of the screen displaying method, furthermore, the new method can process SLR data automatically, which makes it possible to be used in the development of the COMPASS navigation system.

基于激光点云的铁路隧道特征提取及变形分析

本文以隧道扫描点云为主要研究对象,深入探讨三维激光扫描技术在隧道安全监测中的实际应用,采用理论与实验结合的方法,重点分析了平面拟合、点云配准等理论方法的适应性,针对隧道点云配准、特征提取及变形监测等方面做出重点分析,准确获取隧道内壁点、线、面的变形信息,为隧道特征信息及隧道变形信息准确提取提供技术方案和技术支持。

基于激光点云的隧道超欠挖检测与表达

超欠挖是钻爆法隧道施工难以避免的问题,严重的超欠挖将影响施工安全、工程施工成本以及建设质量等,精准的超欠挖检测可以反映隧道爆破开挖质量,为后期支护成本提供依据,保障隧道工程的安全。本文提出一种基于激光点云的隧道超欠挖检测方法,将点云数据投影至断面坐标系,结合设计数据进行超欠挖检测;利用Visual Studio平台开发相应软件,实现超欠挖量、面积和体积的计算与精度评价;调用OpenGL API,以断面图、三维图与平铺图的形式实现超欠挖可视化,结合报表对检测结果进行表达。经过实测数据验证,本文方法的检测结果高效准确,表达效果形象直观,可满足隧道施工过程中超欠挖检测的需求。

钢结构腐蚀损伤的点云局部曲面重构检测方法

为高效检测钢结构中的腐蚀损伤,提出了一种钢结构腐蚀损伤的点云局部曲面重构检测方法。该方法利用统计滤波算法与ICP算法实现点云数据的降噪与配准,根据待检测钢结构点云数据与标准点云模型间的空间关系检测腐蚀范围及深度。除此之外,建立了一种基于邻域搜索的腐蚀类型判断方法,并提出利用K⁃means聚类与Delaunay三角拓扑计算腐蚀损伤面积。通过数值模拟对所提出检测方法进行了精度测试,结果表明:所提方法检测得到的腐蚀范围边界的最大偏差小于1 mm,平均腐蚀深度计算误差低于2%。同时,所提出点云腐蚀类型判断方法的准确率超过98%,腐蚀面积的计算误差低于3%。通过试验进一步验证了所提检测方法的有效性。

轮对廓形采集装置的自适应对中研究

该文针对检修车间内测量轮对全廓形的需求,综合环境、工况、成本和需求等因素,在现有镟前轮对测量设备的基础上,增加补充激光传感法测量的轮对廓形采集装置。考虑轮对测量机测量时会由于轮对车轴抬升高度的不同,导致廓形采集位置不过轴心会对廓形测量数据造成误差的这一问题,该文提出一种基于图像的轮对廓采集装置的自适应对中方法,算法体现对物体表面纹理变化的鲁棒性,大大增加激光这种小目标检测的准确性,检测时间平均每张1.01 s,满足对实时性的要求。实现在不同光照条件影响下,廓形采集装置的快速、精确的自适应调节,提升廓形检测精度的同时为轮对镟修计划编排提供基础。

城市三维模型快速构建关键技术研究

城市三维模型是智慧城市建设的基础,传统的城市三维模型构建过程复杂且耗时,需要花费大量的时间和人力,而且在构建过程中,没有很好地利用已有基础地理信息数据。对此,基于已有基础地理信息数据,经过预处理后作为三维模型的底面数据,结合DEM和激光点云数据获取三维模型的底面高程、建筑高度和建筑物顶部形态等信息,根据定义的规则文件,在挂接通用纹理后快速批量构建三维模型。结果表明,三维模型快速构建法能有效利用已有的数据资源,显著提高三维模型的建模效率。

Cloud Detection and Centroid Extraction of Laser Footprint Image of GF-7 Satellite Laser Altimetry

The laser altimeter loaded on the GaoFen-7(GF-7)satellite is designed to record the full waveform data and footprint image,which can obtain high-precision elevation control points for stereo image.The footprint camera equipped on the GF-7 laser altimetry system can capture the energy distribution at the time of laser emission and the image of the ground object where the laser falls,which can be used to judge whether the laser is affected by the cloud.At the same time,the centroid of laser spot on the footprint image can be extracted to monitor the change of laser pointing stability.In this manuscript,a data quality analysis scheme of laser altimetry based on footprint image is presented.Firstly,the cloud detection of footprint image is realized based on deep learning.The fusion result of the model is about 5%better than that of the traditional cloud detection algorithm,which can quickly and accurately determine whether the laser spot is affected by cloud.Secondly,according to the characteristics of footprint image,a threshold constrained ellipse fitting method for extracting the centroid of laser spot is proposed to monitor the pointing stability of long-period lasers.Based on the above method,the change of laser spot centroid since GF-7 satellite was put into operation is analyzed,and the conclusions obtained have certain reference significance for the quality control of satellite laser altimetry data and the analysis of pointing angle stability.

手持三维激光扫描仪在城市更新立面测量中的应用

随着科技进步及不断演化,手持三维激光扫描仪作为一种高效、高精度的测绘仪器,近年来在各行各业得到了广泛关注和应用。本文针对采用传统仪器对城市更新过程中旧房改造立面测量作业效率低下,且复杂建筑物绘制难度大,精度难以保证等缺点,探讨了手持三维激光扫描仪的技术特点、参数,并重点介绍城市更新旧房改造立面测量技术流程和应用案例分析,最后对手持三维激光扫描仪的应用前景进行展望。本文对提升城市更新旧房改造立面测量技术具有重要意义。

一种基于地面激光雷达点云的树木三维建模方法

为更好地获取树木三维几何结构信息,解决高精度、高还原度的树木三维重建问题,提出了一种基于地面激光雷达(terrestrial laser scanning,TLS)点云数据的树木三维建模方法。针对TLS扫描存在树叶间隙的遮挡,充分考虑叶片聚集,结合叶片和枝干的形态特征,采用Delaunay三角网和Alpha-shape算法分别对树木叶片和枝干进行模型拟合重建,有效克服了过去树木三维建模枝干结构不真实、器官建模不精细等问题,较好实现了对单棵树木叶片和细小枝干的三维重建。所提方法可为森林结构参数获取和资源经营管理等提供技术支撑,同时也能为典型树木的部件级实景三维建模提供一定的借鉴和参考作用。