The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its p...The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.展开更多
In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innova...In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innovation points are reflected in the following aspects:①The proposed algorithm is not dependent on the Schur complement,and the calculation process is simple and clear;②The complexities of time and space tend to O(n)in the context of world point number is far greater than that of images and cameras,so the calculation magnitude and memory consumption can be reduced significantly;③The proposed algorithm can carry out self-calibration bundle adjustment in single-camera,multi-camera,and variable-camera modes;④Some measures are employed to improve the optimization effects.Experimental tests showed that the proposed algorithm has the ability to achieve state-of-the-art performance in accuracy and robustness,and it has a strong adaptability as well,because the optimized results are accurate and robust even if the initial values have large deviations from the truth.This study could provide theoretical guidance and technical support for the image-based positioning and 3D reconstruction in the fields of photogrammetry,computer vision and robotics.展开更多
The solid template CCD camera calibration method of bundle adjustments basedon collinearity equation is presented considering the characteristics of space large-dimensionon-line measurement. In the method, a more comp...The solid template CCD camera calibration method of bundle adjustments basedon collinearity equation is presented considering the characteristics of space large-dimensionon-line measurement. In the method, a more comprehensive camera model is adopted which is based onthe pinhole model extended with distortions corrections. In the process of calibration, calibrationprecision is improved by imaging at different locations in the whole measurement space,multi-imaging at the same location and bundle adjustments optimization. The calibration experimentproves that the calibration method is able to fulfill calibration requirement of CCD camera appliedto vision measurement.展开更多
Bundle adjustment is a camera and point refinement technique in a 3D scene reconstruction pipeline. The camera parameters and the 3D points are refined by minimizing the difference between computed projection and obse...Bundle adjustment is a camera and point refinement technique in a 3D scene reconstruction pipeline. The camera parameters and the 3D points are refined by minimizing the difference between computed projection and observed projection of the image points formulated as a non-linear least-square problem. Levenberg-Marquardt method is used to solve the non-linear least-square problem. Solving the non-linear least-square problem is computationally expensive, proportional to the number of cameras, points, and projections. In this paper, we implement the Bundle Adjustment (BA) algorithm and analyze techniques to improve algorithmic performance by reducing the mean square error. We investigate using an additional radial distortion camera parameter in the BA algorithm and demonstrate better convergence of the mean square error. We also demonstrate the use of explicitly computed analytical derivatives. In addition, we implement the BA algorithm on GPUs using the CUDA parallel programming model to reduce the computational time burden of the BA algorithm. CUDA Streams, atomic operations, and cuBLAS library in the CUDA programming model are proposed, implemented, and demonstrated to improve the performance of the BA algorithm. Our implementation has demonstrated better convergence of the BA algorithm and achieved a speedup of up to 16× on the use of the BA algorithm on various datasets.展开更多
This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision te...This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.展开更多
A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constrai...A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.展开更多
The photogrammetric bundle adjustment was used in data processing of electronic theodolite industrial surveying system by converting angular observations into virtual photo coordinates. The developed algorithm has abi...The photogrammetric bundle adjustment was used in data processing of electronic theodolite industrial surveying system by converting angular observations into virtual photo coordinates. The developed algorithm has ability of precision estimation and data snooping, do not need initial values of exterior orientation elements and object point coordinates. The form of control condition for the system is quite flexible. Neither centering nor leveling is the theodolite needed and the lay out of theodolite position is flexible when the system is used for precise survey. Experiments carried out in test field verify the validity of the data processing method. [展开更多
Inpatients in the intensive care unit（ICU） are at high risk for healthcare-associated infections（HAIs）. In the current study, a bundle of interventions and measures for preventing and controlling HAIs were develop...Inpatients in the intensive care unit（ICU） are at high risk for healthcare-associated infections（HAIs）. In the current study, a bundle of interventions and measures for preventing and controlling HAIs were developed and implemented in the ICU by trained personnel, and the impact of the bundle was evaluated. The incidence of HAIs, the adjusted daily incidence of HAIs and the incidence of three types of catheter-related infections before and after the bundle implementation were compared. The execution rate of the bundle for preventing and controlling ventilator-associated pneumonia（VAP） was increased from 82.06% in 2012 to 96.88% in 2013. The execution rate was increased from 83.03% in 2012 to 91.33% in 2013 for central line-associated bloodstream infection（CLABSI）, from 87.00% to 94.40% for catheter-associated urinary tract infection（CAUTI）, and from 82.05% to 98.55% for multidrug-resistant organisms（MDROs）, respectively. In total, 136 cases（10.37%） in 2012 and 113 cases（7.72%） in 2013 involved HAIs, respectively. Patients suffered from infection of the lower respiratory tract, the most common site of HAIs, in 134 cases（79.29%） in 2012 and 107 cases（74.30%） in 2013 respectively. The incidence of VAP was 32.72‰ and 24.60‰, the number of strains of pathogens isolated was 198 and 173, and the number of MDROs detected in the ICU was 91 and 74 in 2012 and 2013, respectively. The percentage of MDROs among the pathogens causing HAIs was decreased in each quarter of 2013 as compared with the corresponding percentage in 2012. In 2013, the execution rate of the bundle for preventing and controlling HAIs was increased, whereas the incidence of HAIs and VAP decreased as compared with that in 2012.展开更多
A 3D motion and geometric information system of single-antenna radar is proposed,which can be supported by spotlight synthetic aperture radar（SAR） system and inverse SAR（ISAR） system involving relative 3D motion o...A 3D motion and geometric information system of single-antenna radar is proposed,which can be supported by spotlight synthetic aperture radar（SAR） system and inverse SAR（ISAR） system involving relative 3D motion of the rigid target.In this system,applying the geometry invariance of the rigid target,the unknown 3D shape and motion of the radar target can be reconstructed from the 1D range data of some scatterers extracted from the high-resolution range image.Compared with the current 1D-to-3D algorithm,in the proposed algorithm,the requirement of the 1D range data is expanded to incomplete formation involving large angular motion of the target and hence,the quantity of the scatterers and the abundance of 3D motion are enriched.Furthermore,with the three selected affine coordinates fixed,the multi-solution problem of the reconstruction is solved and the technique of nonlinear optimization can be successfully utilized in the system.Two simulations are implemented which verify the higher robustness of the system and the better performance of the 3D reconstruction for the radar target with unknown relative motion.展开更多
Positioning of screw holes is an important production procedure for steel construction connecting with bolts. In this paper, a new production method is presented, in which the digital camera is used for taking picture...Positioning of screw holes is an important production procedure for steel construction connecting with bolts. In this paper, a new production method is presented, in which the digital camera is used for taking pictures of screw holes and other techniques are advanced. This paper also indicates that the pixels of CCD chip in photogrammetry should be chosen as all geometric units in an image, such as interior elements and all kinds of distortions. The measure can also simplify the camera calibration for determining the size of non-square pixel.展开更多
文摘The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.
基金National Natural Science Foundation of China(Nos.41571410,41977067,42171422)。
文摘In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innovation points are reflected in the following aspects:①The proposed algorithm is not dependent on the Schur complement,and the calculation process is simple and clear;②The complexities of time and space tend to O(n)in the context of world point number is far greater than that of images and cameras,so the calculation magnitude and memory consumption can be reduced significantly;③The proposed algorithm can carry out self-calibration bundle adjustment in single-camera,multi-camera,and variable-camera modes;④Some measures are employed to improve the optimization effects.Experimental tests showed that the proposed algorithm has the ability to achieve state-of-the-art performance in accuracy and robustness,and it has a strong adaptability as well,because the optimized results are accurate and robust even if the initial values have large deviations from the truth.This study could provide theoretical guidance and technical support for the image-based positioning and 3D reconstruction in the fields of photogrammetry,computer vision and robotics.
文摘The solid template CCD camera calibration method of bundle adjustments basedon collinearity equation is presented considering the characteristics of space large-dimensionon-line measurement. In the method, a more comprehensive camera model is adopted which is based onthe pinhole model extended with distortions corrections. In the process of calibration, calibrationprecision is improved by imaging at different locations in the whole measurement space,multi-imaging at the same location and bundle adjustments optimization. The calibration experimentproves that the calibration method is able to fulfill calibration requirement of CCD camera appliedto vision measurement.
文摘Bundle adjustment is a camera and point refinement technique in a 3D scene reconstruction pipeline. The camera parameters and the 3D points are refined by minimizing the difference between computed projection and observed projection of the image points formulated as a non-linear least-square problem. Levenberg-Marquardt method is used to solve the non-linear least-square problem. Solving the non-linear least-square problem is computationally expensive, proportional to the number of cameras, points, and projections. In this paper, we implement the Bundle Adjustment (BA) algorithm and analyze techniques to improve algorithmic performance by reducing the mean square error. We investigate using an additional radial distortion camera parameter in the BA algorithm and demonstrate better convergence of the mean square error. We also demonstrate the use of explicitly computed analytical derivatives. In addition, we implement the BA algorithm on GPUs using the CUDA parallel programming model to reduce the computational time burden of the BA algorithm. CUDA Streams, atomic operations, and cuBLAS library in the CUDA programming model are proposed, implemented, and demonstrated to improve the performance of the BA algorithm. Our implementation has demonstrated better convergence of the BA algorithm and achieved a speedup of up to 16× on the use of the BA algorithm on various datasets.
基金the National Natural Science Foundation of China (Nos. 60505017 and 60534070)the Science Planning Project of Zhejiang Province, China (No. 2005C14008)
文摘This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.
基金supported by the National Natural Science Foundations of China (Nos.41101441,60974107, 41471381)the Foundation of Graduate Innovation Center in NUAA(No.kfjj130133)
文摘A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.
文摘The photogrammetric bundle adjustment was used in data processing of electronic theodolite industrial surveying system by converting angular observations into virtual photo coordinates. The developed algorithm has ability of precision estimation and data snooping, do not need initial values of exterior orientation elements and object point coordinates. The form of control condition for the system is quite flexible. Neither centering nor leveling is the theodolite needed and the lay out of theodolite position is flexible when the system is used for precise survey. Experiments carried out in test field verify the validity of the data processing method. [
基金supported by Chinese Nosocomial Infection Control Research Fund(No.ZHYY2013-028)
文摘Inpatients in the intensive care unit（ICU） are at high risk for healthcare-associated infections（HAIs）. In the current study, a bundle of interventions and measures for preventing and controlling HAIs were developed and implemented in the ICU by trained personnel, and the impact of the bundle was evaluated. The incidence of HAIs, the adjusted daily incidence of HAIs and the incidence of three types of catheter-related infections before and after the bundle implementation were compared. The execution rate of the bundle for preventing and controlling ventilator-associated pneumonia（VAP） was increased from 82.06% in 2012 to 96.88% in 2013. The execution rate was increased from 83.03% in 2012 to 91.33% in 2013 for central line-associated bloodstream infection（CLABSI）, from 87.00% to 94.40% for catheter-associated urinary tract infection（CAUTI）, and from 82.05% to 98.55% for multidrug-resistant organisms（MDROs）, respectively. In total, 136 cases（10.37%） in 2012 and 113 cases（7.72%） in 2013 involved HAIs, respectively. Patients suffered from infection of the lower respiratory tract, the most common site of HAIs, in 134 cases（79.29%） in 2012 and 107 cases（74.30%） in 2013 respectively. The incidence of VAP was 32.72‰ and 24.60‰, the number of strains of pathogens isolated was 198 and 173, and the number of MDROs detected in the ICU was 91 and 74 in 2012 and 2013, respectively. The percentage of MDROs among the pathogens causing HAIs was decreased in each quarter of 2013 as compared with the corresponding percentage in 2012. In 2013, the execution rate of the bundle for preventing and controlling HAIs was increased, whereas the incidence of HAIs and VAP decreased as compared with that in 2012.
基金supported by the National Natural Science Foundation of China (60572093)the Doctoral Program of Higher Education(20050004016)the Outstanding Doctoral Science Innovation Foundation of Beijing Jiaotong University (141095522)
文摘A 3D motion and geometric information system of single-antenna radar is proposed,which can be supported by spotlight synthetic aperture radar（SAR） system and inverse SAR（ISAR） system involving relative 3D motion of the rigid target.In this system,applying the geometry invariance of the rigid target,the unknown 3D shape and motion of the radar target can be reconstructed from the 1D range data of some scatterers extracted from the high-resolution range image.Compared with the current 1D-to-3D algorithm,in the proposed algorithm,the requirement of the 1D range data is expanded to incomplete formation involving large angular motion of the target and hence,the quantity of the scatterers and the abundance of 3D motion are enriched.Furthermore,with the three selected affine coordinates fixed,the multi-solution problem of the reconstruction is solved and the technique of nonlinear optimization can be successfully utilized in the system.Two simulations are implemented which verify the higher robustness of the system and the better performance of the 3D reconstruction for the radar target with unknown relative motion.
文摘Positioning of screw holes is an important production procedure for steel construction connecting with bolts. In this paper, a new production method is presented, in which the digital camera is used for taking pictures of screw holes and other techniques are advanced. This paper also indicates that the pixels of CCD chip in photogrammetry should be chosen as all geometric units in an image, such as interior elements and all kinds of distortions. The measure can also simplify the camera calibration for determining the size of non-square pixel.
