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 strat...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.展开更多
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 pr...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.展开更多
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-sca...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.展开更多
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 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.展开更多
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 positio...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.展开更多
Therapeutic effect of bronchisl asthma treated With CO<sub>2</sub> laser irradiating points was ob-served.Ninety-six cases of bronchial asthma,that were considered cold and insufficiency type accord-ing to...Therapeutic effect of bronchisl asthma treated With CO<sub>2</sub> 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 CO<sub>2</sub> 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,FEV<sub>1</sub>.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,CO<sub>2</sub> laser irra-diation is an effective therapy for bronchial asthma.展开更多
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 sensor...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,展开更多
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...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.展开更多
井下斜坡道的定位与建图是实现井下斜坡道无人驾驶的关键技术之一,矿山井下斜坡道区域为典型非结构化环境特征,且道路具有一定倾斜角度,采用传统SLAM算法无法获得精确里程计信息,导致定位与建图精度难以满足无人矿卡行驶需求。针对上述...井下斜坡道的定位与建图是实现井下斜坡道无人驾驶的关键技术之一,矿山井下斜坡道区域为典型非结构化环境特征,且道路具有一定倾斜角度,采用传统SLAM算法无法获得精确里程计信息,导致定位与建图精度难以满足无人矿卡行驶需求。针对上述问题,通过研究激光SLAM(Simultaneous Localization And Mapping)算法LeGO-LOAM,笔者提出一种适用于矿山井下斜坡道环境的定位与建图方法。首先,针对井下斜坡道口两侧均为光滑水泥墙壁,特征点稀少问题,设计了基于人工路标的辅助增强定位方法,有效增加点云特征数量,从而优化位姿估计结果,避免建图漂移现象;然后在特征预处理阶段,提出了一种基于激光点云高度差与坡度信息融合的提取地面点高效算法,通过改善地面地点的选取策略,针对倾斜坑洼路面仍能有效识别地面点,解决了井下斜坡道定位与建图倾斜角度大、误差大等问题;其次,基于CVC(Curved-Voxel Clustering)聚类算法设计了一种斜坡道点云曲率体素聚类算法,采用曲率体素和基于哈希的数据结构对点云进行分割,大幅提高在井下稀疏、噪声环境下点云聚类的鲁棒性;最后,运用Scan-To-Map进行点云匹配,同时兼顾点云配准的性能与速度。在中钢集团山东某井下斜坡道的现场实验证明:与原算法相比精度提升13.15%,Z轴误差降低22.3%,地图质量明显提升,能有效解决井下无人驾驶建图及定位的难题。展开更多
基金founded by National Key R&D Program of China (No.2021YFB2601200)National Natural Science Foundation of China (No.42171416)Teacher Support Program for Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture (No.JDJQ20200307).
文摘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.
基金supported in part by the National Key R&D Program of China(Grant no.2016YFC0401908)。
文摘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.
文摘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.
文摘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.
文摘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.
文摘Therapeutic effect of bronchisl asthma treated With CO<sub>2</sub> 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 CO<sub>2</sub> 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,FEV<sub>1</sub>.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,CO<sub>2</sub> laser irra-diation is an effective therapy for bronchial asthma.
文摘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,
文摘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.
文摘井下斜坡道的定位与建图是实现井下斜坡道无人驾驶的关键技术之一,矿山井下斜坡道区域为典型非结构化环境特征,且道路具有一定倾斜角度,采用传统SLAM算法无法获得精确里程计信息,导致定位与建图精度难以满足无人矿卡行驶需求。针对上述问题,通过研究激光SLAM(Simultaneous Localization And Mapping)算法LeGO-LOAM,笔者提出一种适用于矿山井下斜坡道环境的定位与建图方法。首先,针对井下斜坡道口两侧均为光滑水泥墙壁,特征点稀少问题,设计了基于人工路标的辅助增强定位方法,有效增加点云特征数量,从而优化位姿估计结果,避免建图漂移现象;然后在特征预处理阶段,提出了一种基于激光点云高度差与坡度信息融合的提取地面点高效算法,通过改善地面地点的选取策略,针对倾斜坑洼路面仍能有效识别地面点,解决了井下斜坡道定位与建图倾斜角度大、误差大等问题;其次,基于CVC(Curved-Voxel Clustering)聚类算法设计了一种斜坡道点云曲率体素聚类算法,采用曲率体素和基于哈希的数据结构对点云进行分割,大幅提高在井下稀疏、噪声环境下点云聚类的鲁棒性;最后,运用Scan-To-Map进行点云匹配,同时兼顾点云配准的性能与速度。在中钢集团山东某井下斜坡道的现场实验证明:与原算法相比精度提升13.15%,Z轴误差降低22.3%,地图质量明显提升,能有效解决井下无人驾驶建图及定位的难题。
