针对菇房内杏鲍菇表型参数测量任务中,由于扫描设备视角受限,扫描的杏鲍菇点云出现残缺问题,基于AdaPoinTr(Adaptive geometry-aware point transformers)提出了改进的SwinPoinTr模型,实现了对残缺杏鲍菇点云的准确补全和杏鲍菇表型参...针对菇房内杏鲍菇表型参数测量任务中,由于扫描设备视角受限,扫描的杏鲍菇点云出现残缺问题,基于AdaPoinTr(Adaptive geometry-aware point transformers)提出了改进的SwinPoinTr模型,实现了对残缺杏鲍菇点云的准确补全和杏鲍菇表型参数的测量。该方法在使用提出的特征重塑模块的基础上,构建具有几何感知能力的层次化Transformer编码模块,提高了模型对输入点云的利用率和模型捕捉点云细节特征的能力。然后基于泊松重建方法完成了补全点云表面重建,并测量到杏鲍菇表型参数。实验结果表明,本文所提算法在残缺杏鲍菇点云补全任务中,模型倒角距离为1.316×10^(-4),地球移动距离为21.3282,F1分数为87.87%。在表型参数估测任务中,模型对杏鲍菇菌高、体积、表面积估测结果的决定系数分别为0.9582、0.9596、0.9605,均方根误差分别为4.4213 mm、10.8185 cm^(3)、7.5778 cm^(2)。结果证实了该研究方法可以有效地补全残缺的杏鲍菇点云,可以为菇房内杏鲍菇表型参数测量提供基础。展开更多
The missile-borne LiDAR has an essential prospect in precise guidance.However,the instability of the missile has a significant impact on the precision of LIDAR point cloud,thus modeling and analyzing the influencing f...The missile-borne LiDAR has an essential prospect in precise guidance.However,the instability of the missile has a significant impact on the precision of LIDAR point cloud,thus modeling and analyzing the influencing factors of point cloud generation is necessary.In this investigation,the authors modeled the point cloud calculation process of missile-borne linear array scanning LiDAR under ideal conditions and analyzed the effect of position change on the fleld of view(FOV) in the course of platform motion.Subsequently,the authors summarized that the stability concerning the field of view and the target tracking are dependent on three limiting conditions.Finally,the authors derived an error formula and analyzed several typical errors in missile platform flight,including scanner error,POS error,system integration error,and platform vibration error.Based on theo retical analysis and simulation experiments,the model proposed in this papier can provide a theoretical basis for the design of the missile-borne LiDAR system and the selection of related instruments in practice.展开更多
In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technolog...In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.展开更多
基金financially supported by the China National Natural Science Foundation(Grant No.61871389)the Research Plan Project of the National University of Defense Technology(Grant No.ZK18-01-02)the Director Foundation of State Key Laboratory of Pulsed Power Laser Technology(Grant No.SKL2018ZR09)。
文摘The missile-borne LiDAR has an essential prospect in precise guidance.However,the instability of the missile has a significant impact on the precision of LIDAR point cloud,thus modeling and analyzing the influencing factors of point cloud generation is necessary.In this investigation,the authors modeled the point cloud calculation process of missile-borne linear array scanning LiDAR under ideal conditions and analyzed the effect of position change on the fleld of view(FOV) in the course of platform motion.Subsequently,the authors summarized that the stability concerning the field of view and the target tracking are dependent on three limiting conditions.Finally,the authors derived an error formula and analyzed several typical errors in missile platform flight,including scanner error,POS error,system integration error,and platform vibration error.Based on theo retical analysis and simulation experiments,the model proposed in this papier can provide a theoretical basis for the design of the missile-borne LiDAR system and the selection of related instruments in practice.
文摘In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.
