Augmented reality(AR)is an emerging dynamic technology that effectively supports education across different levels.The increased use of mobile devices has an even greater impact.As the demand for AR applications in ed...Augmented reality(AR)is an emerging dynamic technology that effectively supports education across different levels.The increased use of mobile devices has an even greater impact.As the demand for AR applications in education continues to increase,educators actively seek innovative and immersive methods to engage students in learning.However,exploring these possibilities also entails identifying and overcoming existing barriers to optimal educational integration.Concurrently,this surge in demand has prompted the identification of specific barriers,one of which is three-dimensional(3D)modeling.Creating 3D objects for augmented reality education applications can be challenging and time-consuming for the educators.To address this,we have developed a pipeline that creates realistic 3D objects from the two-dimensional(2D)photograph.Applications for augmented and virtual reality can then utilize these created 3D objects.We evaluated the proposed pipeline based on the usability of the 3D object and performance metrics.Quantitatively,with 117 respondents,the co-creation team was surveyed with openended questions to evaluate the precision of the 3D object created by the proposed photogrammetry pipeline.We analyzed the survey data using descriptive-analytical methods and found that the proposed pipeline produces 3D models that are positively accurate when compared to real-world objects,with an average mean score above 8.This study adds new knowledge in creating 3D objects for augmented reality applications by using the photogrammetry technique;finally,it discusses potential problems and future research directions for 3D objects in the education sector.展开更多
0 INTRODUCTION Rock masses are inherently discontinuous,with fractures and joints governing their mechanical behavior and stability(Liu et al.,2024;Shang et al.,2018;Lisjak and Grasselli,2014;Scholtès and Donz...0 INTRODUCTION Rock masses are inherently discontinuous,with fractures and joints governing their mechanical behavior and stability(Liu et al.,2024;Shang et al.,2018;Lisjak and Grasselli,2014;Scholtès and Donzé,2012;Jiang et al.,2009;Pine et al.,2006;Aydan et al.,1989).展开更多
Stem volume estimation is crucial in forest ecology and management,particularly for timber harvesting strategies and carbon stock assessments.This study aimed to develop a variable-exponent taper equation specifically...Stem volume estimation is crucial in forest ecology and management,particularly for timber harvesting strategies and carbon stock assessments.This study aimed to develop a variable-exponent taper equation specifically tailored to savanna tree species using close-range photogrammetry(CRP)data and to evaluate its performance against conventional volume equations for stem volume estimation.A dataset of 30 trees across five dominant savanna species was used to fit the taper model,which was validated using a separate dataset of 322 trees from 14 species.The results demonstrated significant improvements in volume estimation accuracy when using the taper equation.At the tree level,the root mean square error(RMSE)decreased by 47%,from 598 to 319 dm^(3),and the mean absolute bias(MAB)by 48%,from 328 to 172 dm3,compared to volume equations.Similarly,at the plot level,RMSE was reduced by 42% and MAB by 40%.The model performed well for species with regular forms.However,species with irregular tapers exhibited higher errors,reflecting the challenges of modeling stem forms of mixed species.The use of CRP proved valuable,providing high-resolution diameter measurements that improved model parameterization.This study underscores the importance of advanced data collection methods for enhancing taper model accuracy and suggests that further species-specific adjustments are needed to improve performance for species with irregular forms.The findings support the broader application of taper equations for improving stem volume estimates in savanna ecosystems,contributing to better forest management and resource monitoring practices.展开更多
Potholes are the most prevalent type of structural defect found on roads,caused by aging infrastructure,heavy rains,heavy traffic,thin or weak substructures,and other factors.Regular assessment of road conditions is e...Potholes are the most prevalent type of structural defect found on roads,caused by aging infrastructure,heavy rains,heavy traffic,thin or weak substructures,and other factors.Regular assessment of road conditions is essential for maintaining and improving road networks.Current techniques for identifying potholes on urban roadways primarily rely on public reporting,such as hotlines or social networking websites,which are both timeconsuming and inefficient.This study aims to detect potholes using Unmanned Aerial Vehicles(UAVs)images,enabling accurate analysis of their size,shape,and location,thereby enhancing detection efficiency compared to conventional methods.It compared area and volume measurements of potholes derived from UAV models with those obtained through traditional methods,revealing discrepancies and highlighting UAVs’potential for providing more accurate data with appropriate settings.The study found measurement errors ranging from 90 to 8200 cm^(2) in area and 2000 to 31,000 cm^(3) in volume,emphasizing the need for careful data handling in assessments.This study demonstrates UAV technology’s effectiveness in pothole detection,providing insights that support the adoption of aerial photogrammetry for road maintenance.This approach has the potential to improve efficiency in infrastructure management.By appropriately adjusting altitude settings and parameters based on pothole size and depth,UAVs can detect potholes effectively.To achieve more accurate results,the study recommends analyzing a larger number of potholes rather than limiting the focus to a single pothole.展开更多
The estimation of orientation parameters and correction of lens distortion are crucial problems in the field of Unmanned Aerial Vehicles(UAVs)photogrammetry.In recent years,the utilization of UAVs for aerial photogram...The estimation of orientation parameters and correction of lens distortion are crucial problems in the field of Unmanned Aerial Vehicles(UAVs)photogrammetry.In recent years,the utilization of UAVs for aerial photogrammetry has witnessed a surge in popularity.Typically,UAVs are equipped with low-cost non-metric cameras and a Position and Orientation System(POS).Unfortunately,the Interior Orientation Parameters(IOPs)of the non-metric cameras are not fixed.Whether the lens distortions are large or small,they effect the image coordinates accordingly.Additionally,Inertial Measurement Units(IMUs)often have observation errors.To address these challenges and improve parameter estimation for UAVs Light Detection and Ranging(LiDAR)and photogrammetry,this paper analyzes the accuracy of POS observations obtained from Global Navigation Satellite System Real Time Kinematic(GNSS-RTK)and IMU data.A method that incorporates additional known conditions for parameter estimation,a series of algorithms to simultaneously solve for IOPs,Exterior Orientation Parameters(EOPs),and camera lens distortion correction parameters are proposed.Extensive experiments demonstrate that the coordinates measured by GNSS-RTK can be directly used as linear EOPs;however,angular EOP measurements from IMUs exhibit relatively large errors compared to adjustment results and require correction during the adjustment process.The IOPs of non-metric cameras vary slightly between images but need to be treated as unknown parameters in high precision applications.Furthermore,it is found that the Ebner systematic error model is sensitive to the choice of the magnification parameter of the photographic baseline length in images,it should be set as less than or equal to one third of the photographic baseline to ensure stable solutions.展开更多
多相机三维数字图像相关(three-dimensional digital image correlation,3D-DIC)系统在测量核燃料包壳管应变的实际应用中,多相机标定环节存在坐标系转换引发的累计误差增加及全局优化能力不足等问题。为此,提出一种基于空间标定靶的多...多相机三维数字图像相关(three-dimensional digital image correlation,3D-DIC)系统在测量核燃料包壳管应变的实际应用中,多相机标定环节存在坐标系转换引发的累计误差增加及全局优化能力不足等问题。为此,提出一种基于空间标定靶的多相机全局标定方法。首先,提出为各相机在标定靶每个位姿下提供外方位参数初值的方法,保证空间后方交会正确收敛;其次,提出多相机多位姿光束平差(bundle adjustment,BA)方法,保证多相机标定精度达到全局最优。实验结果表明,该方法的标定精度较直接线性变换(direct linear transformation,DLT)方法提高了55.1%,最大位移误差标准差降低了16.3%。同时,该方法无需对标志点进行手动编号,使标定过程实现了自动化,标定效率更高。展开更多
[Objective] The aim was to explore the measurement of coordinate parameter by multi-baseline digital close-range photogrammetry system.[Method] The 3-dimensional coordinate of 8-year-old Jujube was measured by using L...[Objective] The aim was to explore the measurement of coordinate parameter by multi-baseline digital close-range photogrammetry system.[Method] The 3-dimensional coordinate of 8-year-old Jujube was measured by using Lensphoto multi-baseline digital close-range photogrammetry system,and through comparing with measured data of Total Station,the error and accuracy of photogrammetry data were analyzed.[Result] The absolute error of X,Y and Z coordinate was 0-0.014,0-0.018 and 0-0.004 m respectively,and the relative error of X,Y and Z coordinate was less than 0.145%.The significance test of pairs for the photogrammetry data and measured data of Total Station indicated that the space coordinate data of stumpage were accurately measured by using the multi-baseline digital close-range photogrammetry method,and the photogrammetry data meet the need of space coordinate measurement for virtual plant growth simulation.[Conclusion] This study had provided theoretical basis for the growth measurement of virtual plant growth simulation.展开更多
文摘Augmented reality(AR)is an emerging dynamic technology that effectively supports education across different levels.The increased use of mobile devices has an even greater impact.As the demand for AR applications in education continues to increase,educators actively seek innovative and immersive methods to engage students in learning.However,exploring these possibilities also entails identifying and overcoming existing barriers to optimal educational integration.Concurrently,this surge in demand has prompted the identification of specific barriers,one of which is three-dimensional(3D)modeling.Creating 3D objects for augmented reality education applications can be challenging and time-consuming for the educators.To address this,we have developed a pipeline that creates realistic 3D objects from the two-dimensional(2D)photograph.Applications for augmented and virtual reality can then utilize these created 3D objects.We evaluated the proposed pipeline based on the usability of the 3D object and performance metrics.Quantitatively,with 117 respondents,the co-creation team was surveyed with openended questions to evaluate the precision of the 3D object created by the proposed photogrammetry pipeline.We analyzed the survey data using descriptive-analytical methods and found that the proposed pipeline produces 3D models that are positively accurate when compared to real-world objects,with an average mean score above 8.This study adds new knowledge in creating 3D objects for augmented reality applications by using the photogrammetry technique;finally,it discusses potential problems and future research directions for 3D objects in the education sector.
基金supported by the National Key R&D Program of China(No.2022YFC3080200)。
文摘0 INTRODUCTION Rock masses are inherently discontinuous,with fractures and joints governing their mechanical behavior and stability(Liu et al.,2024;Shang et al.,2018;Lisjak and Grasselli,2014;Scholtès and Donzé,2012;Jiang et al.,2009;Pine et al.,2006;Aydan et al.,1989).
基金partially funded by the International Foundation for Science(Grant No:I-1-D-6066-1).
文摘Stem volume estimation is crucial in forest ecology and management,particularly for timber harvesting strategies and carbon stock assessments.This study aimed to develop a variable-exponent taper equation specifically tailored to savanna tree species using close-range photogrammetry(CRP)data and to evaluate its performance against conventional volume equations for stem volume estimation.A dataset of 30 trees across five dominant savanna species was used to fit the taper model,which was validated using a separate dataset of 322 trees from 14 species.The results demonstrated significant improvements in volume estimation accuracy when using the taper equation.At the tree level,the root mean square error(RMSE)decreased by 47%,from 598 to 319 dm^(3),and the mean absolute bias(MAB)by 48%,from 328 to 172 dm3,compared to volume equations.Similarly,at the plot level,RMSE was reduced by 42% and MAB by 40%.The model performed well for species with regular forms.However,species with irregular tapers exhibited higher errors,reflecting the challenges of modeling stem forms of mixed species.The use of CRP proved valuable,providing high-resolution diameter measurements that improved model parameterization.This study underscores the importance of advanced data collection methods for enhancing taper model accuracy and suggests that further species-specific adjustments are needed to improve performance for species with irregular forms.The findings support the broader application of taper equations for improving stem volume estimates in savanna ecosystems,contributing to better forest management and resource monitoring practices.
基金Ministry of Higher Education(MOHE)are greatly acknowledged for providing the Fundamental Research Grant Scheme(Grant No.FRGS/1/2021/WAB07/UITM/02/2)GPK fund(Grant No.600-RMC/GPK 5/3(223/2020))College of Built Environment,Universiti Teknologi MARA(UiTM)and Research Management Centre(RMC)to enable this research to be carried out.
文摘Potholes are the most prevalent type of structural defect found on roads,caused by aging infrastructure,heavy rains,heavy traffic,thin or weak substructures,and other factors.Regular assessment of road conditions is essential for maintaining and improving road networks.Current techniques for identifying potholes on urban roadways primarily rely on public reporting,such as hotlines or social networking websites,which are both timeconsuming and inefficient.This study aims to detect potholes using Unmanned Aerial Vehicles(UAVs)images,enabling accurate analysis of their size,shape,and location,thereby enhancing detection efficiency compared to conventional methods.It compared area and volume measurements of potholes derived from UAV models with those obtained through traditional methods,revealing discrepancies and highlighting UAVs’potential for providing more accurate data with appropriate settings.The study found measurement errors ranging from 90 to 8200 cm^(2) in area and 2000 to 31,000 cm^(3) in volume,emphasizing the need for careful data handling in assessments.This study demonstrates UAV technology’s effectiveness in pothole detection,providing insights that support the adoption of aerial photogrammetry for road maintenance.This approach has the potential to improve efficiency in infrastructure management.By appropriately adjusting altitude settings and parameters based on pothole size and depth,UAVs can detect potholes effectively.To achieve more accurate results,the study recommends analyzing a larger number of potholes rather than limiting the focus to a single pothole.
基金Natural Science Foundation of Hunan Province,China(No.2024JJ8335)Open Topic of Hunan Geospatial Information Engineering and Technology Research Center,China(No.HNGIET2023004).
文摘The estimation of orientation parameters and correction of lens distortion are crucial problems in the field of Unmanned Aerial Vehicles(UAVs)photogrammetry.In recent years,the utilization of UAVs for aerial photogrammetry has witnessed a surge in popularity.Typically,UAVs are equipped with low-cost non-metric cameras and a Position and Orientation System(POS).Unfortunately,the Interior Orientation Parameters(IOPs)of the non-metric cameras are not fixed.Whether the lens distortions are large or small,they effect the image coordinates accordingly.Additionally,Inertial Measurement Units(IMUs)often have observation errors.To address these challenges and improve parameter estimation for UAVs Light Detection and Ranging(LiDAR)and photogrammetry,this paper analyzes the accuracy of POS observations obtained from Global Navigation Satellite System Real Time Kinematic(GNSS-RTK)and IMU data.A method that incorporates additional known conditions for parameter estimation,a series of algorithms to simultaneously solve for IOPs,Exterior Orientation Parameters(EOPs),and camera lens distortion correction parameters are proposed.Extensive experiments demonstrate that the coordinates measured by GNSS-RTK can be directly used as linear EOPs;however,angular EOP measurements from IMUs exhibit relatively large errors compared to adjustment results and require correction during the adjustment process.The IOPs of non-metric cameras vary slightly between images but need to be treated as unknown parameters in high precision applications.Furthermore,it is found that the Ebner systematic error model is sensitive to the choice of the magnification parameter of the photographic baseline length in images,it should be set as less than or equal to one third of the photographic baseline to ensure stable solutions.
文摘多相机三维数字图像相关(three-dimensional digital image correlation,3D-DIC)系统在测量核燃料包壳管应变的实际应用中,多相机标定环节存在坐标系转换引发的累计误差增加及全局优化能力不足等问题。为此,提出一种基于空间标定靶的多相机全局标定方法。首先,提出为各相机在标定靶每个位姿下提供外方位参数初值的方法,保证空间后方交会正确收敛;其次,提出多相机多位姿光束平差(bundle adjustment,BA)方法,保证多相机标定精度达到全局最优。实验结果表明,该方法的标定精度较直接线性变换(direct linear transformation,DLT)方法提高了55.1%,最大位移误差标准差降低了16.3%。同时,该方法无需对标志点进行手动编号,使标定过程实现了自动化,标定效率更高。
基金Supported by National Natural Science Foundation of China(30770401)National Eleventh Five-Year Plan for Forestry Scienceand Technology Support Topics(2006BADO3A0505)~~
文摘[Objective] The aim was to explore the measurement of coordinate parameter by multi-baseline digital close-range photogrammetry system.[Method] The 3-dimensional coordinate of 8-year-old Jujube was measured by using Lensphoto multi-baseline digital close-range photogrammetry system,and through comparing with measured data of Total Station,the error and accuracy of photogrammetry data were analyzed.[Result] The absolute error of X,Y and Z coordinate was 0-0.014,0-0.018 and 0-0.004 m respectively,and the relative error of X,Y and Z coordinate was less than 0.145%.The significance test of pairs for the photogrammetry data and measured data of Total Station indicated that the space coordinate data of stumpage were accurately measured by using the multi-baseline digital close-range photogrammetry method,and the photogrammetry data meet the need of space coordinate measurement for virtual plant growth simulation.[Conclusion] This study had provided theoretical basis for the growth measurement of virtual plant growth simulation.
