Web-like obstacles,such as safety nets,represent a unique hazard for drones,and especially UAVs(Unmanned Aerial Vehicles).Fencing and netting are particularly difficult to distinguish from the background using either ...Web-like obstacles,such as safety nets,represent a unique hazard for drones,and especially UAVs(Unmanned Aerial Vehicles).Fencing and netting are particularly difficult to distinguish from the background using either computer vision,lidar and sonar.In contrast,animals such as flying insects may detect these web-like obstacles using Optic Flow(OF),and more precisely motion parallax.A netting-avoidance solution was proposed using a OF-based detection method.The netting detection method was based on a signature defined by the shape of the OF magnitude across the visual field.We established that the OF shape depends on the orientation of the netting in relation to the hexarotor’s movement.This paper demonstrates netting detection in real-world experiments,according to any direction flight made by the UAV along the net.The proposed NOWA method(which stands for Netting Optical floW-based distinction Algorithm)separates the OF signatures belonging to these different surfaces-netting or background-whatever their orientations.By extracting the OF signatures of these different surfaces and separating them,the proposed visual method can estimate their relative locations and orientations.In a robotic simulations,the multirotor explores and navigates automatically using this netting detection method,using saccades to avoid obstacles.In the simulations,these saccades are also used to simplify netting detection by orienting itself systematically parallel to these planes,a behavior reminiscent of flying insects.展开更多
The ability to localize moving objects within the environment is critical for autonomous robotic systems. This paper describes a moving object detection and localization system using multiple robots equipped with inex...The ability to localize moving objects within the environment is critical for autonomous robotic systems. This paper describes a moving object detection and localization system using multiple robots equipped with inexpensive optic flow sensors. We demonstrate an architecture capable of detecting motion along a plane by collecting three sets of one-dimensional optic flow data. The detected object is then localized with respect to each of the robots in the system.展开更多
This study proposes a novel radar echo extrapolation algorithm,OF-ConvGRU,which integrates Optical Flow(OF)and Convolutional Gated Recurrent Unit(ConvGRU)methods for improved nowcasting.Using the Standardized Radar Da...This study proposes a novel radar echo extrapolation algorithm,OF-ConvGRU,which integrates Optical Flow(OF)and Convolutional Gated Recurrent Unit(ConvGRU)methods for improved nowcasting.Using the Standardized Radar Dataset of the Guangdong-Hong Kong-Macao Greater Bay Area,the performance of OF-ConvGRU was evaluated against OF and ConvGRU methods.Threat Score(TS)and Bias Score(BIAS)were employed to assess extrapolation accuracy across various echo intensities(20-50 dBz)and weather phenomena.Results demonstrate that OF-ConvGRU significantly enhances prediction accuracy for moderate-intensity echoes(30-40 dBz),effectively combining OF s precise motion estimation with ConvGRU s nonlinear learning capabilities.However,challenges persist in low-intensity(20 dBz)and high-intensity(50 dBz)echo predictions.The study reveals distinct advantages of each method in specific contexts,highlighting the importance of multi-method approaches in operational nowcasting.OF-ConvGRU shows promise in balancing short-term accuracy with long-term stability,particularly for complex weather systems.展开更多
Underwater target motion estimation is a challenge for ocean military and scientific research.In this work,we propose a method based on the combination of polarization imaging and optical flow for turbid underwater ta...Underwater target motion estimation is a challenge for ocean military and scientific research.In this work,we propose a method based on the combination of polarization imaging and optical flow for turbid underwater target detection.Polarization imaging can reduce the influence of backscattered light and obtain high-quality images underwater.The optical flow shows the motion and structural information of the target.We use polarized optical flow to obtain the optical flow field and estimate the target motion.The experimental results of different targets under varying water turbidity levels illustrate that our method is realizable and robust.The precision is verified by comparing the results with the precise displacement data and calculating two error measures.The proposed method based on polarized optical flow can obtain accurate displacement information and a good recognition effect.Moving target segmentation based on the Otsu method further proves the superiority of the polarized optical flow under turbid water.This study is valuable for target detection and motion estimation in scattering environments.展开更多
To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizi...To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.展开更多
Objective:The goal of this study was to examine the prognostic performance of optical flow ratio(OFR)among patients with coronary artery disease(CAD)after percutaneous coronary intervention(PCI).Methods:We recruited p...Objective:The goal of this study was to examine the prognostic performance of optical flow ratio(OFR)among patients with coronary artery disease(CAD)after percutaneous coronary intervention(PCI).Methods:We recruited patients with CAD undergoing optical coherence tomography(OCT)-directed PCI between January 2019 and June 2021 for our single-center,hospital-based,retrospective cohort investigation.We assessed the link between post-PCI OFR and major adverse cardiovascular events(MACE)via multivariate Cox regression analy-sis.Results:Receiver operating characteristic analysis revealed that the best post-PCI OFR threshold for MACE was 0.91,and introduction of OFR into the baseline profile and OCT results markedly enhanced MACE identification after PCI.On the basis of survival curves,patients with OFR≤0.91(P<0.001)and thin-cap fibroatheroma(TCFA)(P=0.007)exhibited higher MACE incidence,and myocardial infarction(MI)incidence was considerably greater among patients with OFR≤0.91(P<0.001),compared with OFR>0.91.Multivariate Cox regression analysis suggested that OFR≤0.91(hazard ratio[HR]:3.60;95%confidence interval[CI]:1.24–10.44;P=0.019),and TCFA(HR:3.63;95%CI:1.42–9.20;P=0.007)were independent risk factors for MACE,and OFR≤0.91 was independently associated with MI(HR:14.64;95%CI:3.27–65.54;P<0.001).Conclusion:OFR after PCI is an independent MACE bio-indicator among patients with CAD.Adding OFR to post-PCI OCT results may potentially enhance MACE prediction.展开更多
Using traditional particle tracking velocimetry based on optical flow for measuring areas with large velocity gradient changes may cause oversmoothing,resulting in significant measurement errors.To address this proble...Using traditional particle tracking velocimetry based on optical flow for measuring areas with large velocity gradient changes may cause oversmoothing,resulting in significant measurement errors.To address this problem,the traditional particle tracking velocimetry method based on an optical flow was improved.The level set segmentation algorithm was used to obtain the boundary contour of the region with large velocity gradient changes,and the non-uniform flow field was divided into regions according to the boundary contour to obtain sub-regions with uniform velocity distribution.The particle tracking velocimetry method based on optical flow was used to measure the granular flow velocity in each sub-region,thus avoiding the problem of granular flow distribution.The simulation results show that the measurement accuracy of this method is approximately 10%higher than that of traditional methods.The method was applied to a velocity measurement experiment on dense granular flow in silos,and the velocity distribution of the granular flow was obtained,verifying the practicality of the method in granular flow fields.展开更多
Current deformation measurement techniques suffer from limited spatial resolution. In this work, a highly accurate and high-resolution Horn Schunck optical flow method is developed and then applied to measuring the st...Current deformation measurement techniques suffer from limited spatial resolution. In this work, a highly accurate and high-resolution Horn Schunck optical flow method is developed and then applied to measuring the static deformation of a birdlike flexible airfoil at a series of angles of attack at Reynolds number 100,000 in a low speed, low noise wind tunnel. To allow relatively large displacements, a nonlinear Horn-Schunck model and a coarse-to-fine warping process are adopted. To preserve optical flow discontinuities, a nonquadratic penalization function, a multi- cue driven bilateral filtering and a principle component analysis of local image patterns are used. First, the accuracy and convergence of this Horn-Schunck technique are verified on a benchmark. Then, the maximum displacement that can be reliably calculated by this technique is studied on synthetic images. Both studies are compared with the performance of a Lucas-Kanade optical flow method. Finally, the Horn-Schunck technique is used to estimate the 3-D deformation of the birdlike airfoil through a stereoscopic camera setup. The results are compared with those computed by Lucas-Kanade optical flow, image correlation and numerical simulation.展开更多
The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Far...The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Farneback algorithm is used to calculate the optical flow field of the first-view video frames taken by the on-board image transmission camera.Based on the optical flow information,a fuzzy obstacle avoidance controller is then designed to generate the FWAV steering commands.Experimental results show that the proposed obstacle avoidance method can accurately identify obstacles and achieve obstacle avoidance for FWAVs.展开更多
This paper focuses mainly on semi-strapdown image homing guided （SSIHG） system design based on optical flow for a six-degree-of-freedom （6-DOF） axial-symmetric skid-to-turn missile. Three optical flow algorithms s...This paper focuses mainly on semi-strapdown image homing guided （SSIHG） system design based on optical flow for a six-degree-of-freedom （6-DOF） axial-symmetric skid-to-turn missile. Three optical flow algorithms suitable for large displacements are introduced and compared. The influence of different displacements on computational accuracy of the three algorithms is analyzed statistically. The total optical flow of the SSIHG missile is obtained using the Scale Invariant Feature Transform （SIFT） algorithm, which is the best among the three for large displacements. After removing the rotational optical flow caused by rotation of the gimbal and missile body from the total optical flow, the remaining translational optical flow is smoothed via Kalman filtering. The circular navigation guidance （CNG） law with impact angle constraint is then obtained utilizing the smoothed translational optical flow and position of the target image. Simulations are carried out under both disturbed and undisturbed conditions, and results indicate the proposed guidance strategy for SSIHG missiles can result in a precise target hit with a desired impact angle without the need for the time-to-go parameter.展开更多
Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the air...Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.展开更多
A modification of Horn and Schunk＇s approach is investigated, which leads to a better preservation of flow discontinuities. It improves Horn-Schunk model in three aspects： （1） It replaces the smooth weight coeffic...A modification of Horn and Schunk＇s approach is investigated, which leads to a better preservation of flow discontinuities. It improves Horn-Schunk model in three aspects： （1） It replaces the smooth weight coefficient in the energy equation by the variable weight coefficient. （2） It adopts a novel method to compute the mean velocity. The novel method also reflects the effect of the intensity difference on the image velocity diffusion. （3） It introduces a more efficient iterative method than the Gauss-Seidel method to solve the associated Euler-Lagrange equation. The experiment results validate the better effect of the improved method on preserving discontinuities.展开更多
Globally exponential stability （which implies convergence and uniqueness） of their classical iterative algorithm is established using methods of heat equations and energy integral after embedding the discrete iterat...Globally exponential stability （which implies convergence and uniqueness） of their classical iterative algorithm is established using methods of heat equations and energy integral after embedding the discrete iteration into a continuous flow. The stability condition depends explicitly on smoothness of the image sequence, size of image domain, value of the regularization parameter, and finally discretization step. Specifically, as the discretization step approaches to zero, stability holds unconditionally. The analysis also clarifies relations among the iterative algorithm, the original variation formulation and the PDE system. The proper regularity of solution and natural images is briefly surveyed and discussed. Experimental results validate the theoretical claims both on convergence and exponential stability.展开更多
Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate...Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.展开更多
A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relat...A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.展开更多
基金The participation of X.D.in this research was made possible by the joint PhD grant from the Agence Innovation Défense(AID)and Aix-Marseille UniversityFinancial support for the running costs was provided via a ProxiLearn project grant(ANR-19-ASTR-0009)to F.R.+2 种基金via SpotReturn project grant(ANR-21-ASRO-0001-02)to T.R.and F.R.from the ANR(Astrid Program)X.D.and F.R.were also supported by Aix Marseille University and the CNRS(Life Science,Information Science,and Engineering and Science&technology Institutes)The facilities for the experimental tests has been mainly provided by ROBOTEX 2.0(Grants ROBOTEX ANR-10-EQPX-44-01 and TIRREX ANR-21-ESRE-0015).
文摘Web-like obstacles,such as safety nets,represent a unique hazard for drones,and especially UAVs(Unmanned Aerial Vehicles).Fencing and netting are particularly difficult to distinguish from the background using either computer vision,lidar and sonar.In contrast,animals such as flying insects may detect these web-like obstacles using Optic Flow(OF),and more precisely motion parallax.A netting-avoidance solution was proposed using a OF-based detection method.The netting detection method was based on a signature defined by the shape of the OF magnitude across the visual field.We established that the OF shape depends on the orientation of the netting in relation to the hexarotor’s movement.This paper demonstrates netting detection in real-world experiments,according to any direction flight made by the UAV along the net.The proposed NOWA method(which stands for Netting Optical floW-based distinction Algorithm)separates the OF signatures belonging to these different surfaces-netting or background-whatever their orientations.By extracting the OF signatures of these different surfaces and separating them,the proposed visual method can estimate their relative locations and orientations.In a robotic simulations,the multirotor explores and navigates automatically using this netting detection method,using saccades to avoid obstacles.In the simulations,these saccades are also used to simplify netting detection by orienting itself systematically parallel to these planes,a behavior reminiscent of flying insects.
文摘The ability to localize moving objects within the environment is critical for autonomous robotic systems. This paper describes a moving object detection and localization system using multiple robots equipped with inexpensive optic flow sensors. We demonstrate an architecture capable of detecting motion along a plane by collecting three sets of one-dimensional optic flow data. The detected object is then localized with respect to each of the robots in the system.
基金Scientific Research and Development Project of Hebei Meteorological Bureau(23ky08).
文摘This study proposes a novel radar echo extrapolation algorithm,OF-ConvGRU,which integrates Optical Flow(OF)and Convolutional Gated Recurrent Unit(ConvGRU)methods for improved nowcasting.Using the Standardized Radar Dataset of the Guangdong-Hong Kong-Macao Greater Bay Area,the performance of OF-ConvGRU was evaluated against OF and ConvGRU methods.Threat Score(TS)and Bias Score(BIAS)were employed to assess extrapolation accuracy across various echo intensities(20-50 dBz)and weather phenomena.Results demonstrate that OF-ConvGRU significantly enhances prediction accuracy for moderate-intensity echoes(30-40 dBz),effectively combining OF s precise motion estimation with ConvGRU s nonlinear learning capabilities.However,challenges persist in low-intensity(20 dBz)and high-intensity(50 dBz)echo predictions.The study reveals distinct advantages of each method in specific contexts,highlighting the importance of multi-method approaches in operational nowcasting.OF-ConvGRU shows promise in balancing short-term accuracy with long-term stability,particularly for complex weather systems.
基金supported by the National Natural Science Foundation of China (No.52394252)the Postdoctoral Fellowship Program of CPSF (No.GZC20232497)+2 种基金the Key Research and Development Program of Shandong Province,China (No.2021ZLGX04)the Shandong Postdoctoral Science Foundation (No.SDBX2023012)the Qingdao Postdoctoral Program Grant (No.QDBSH20230202009)。
文摘Underwater target motion estimation is a challenge for ocean military and scientific research.In this work,we propose a method based on the combination of polarization imaging and optical flow for turbid underwater target detection.Polarization imaging can reduce the influence of backscattered light and obtain high-quality images underwater.The optical flow shows the motion and structural information of the target.We use polarized optical flow to obtain the optical flow field and estimate the target motion.The experimental results of different targets under varying water turbidity levels illustrate that our method is realizable and robust.The precision is verified by comparing the results with the precise displacement data and calculating two error measures.The proposed method based on polarized optical flow can obtain accurate displacement information and a good recognition effect.Moving target segmentation based on the Otsu method further proves the superiority of the polarized optical flow under turbid water.This study is valuable for target detection and motion estimation in scattering environments.
文摘To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.
基金supported by the Outstanding Young Talent Program of Guangdong Provincial People’s Hospital(grant number KJ012019084)the High-level Hospital Construction Project(grant number DFJH2020021).
文摘Objective:The goal of this study was to examine the prognostic performance of optical flow ratio(OFR)among patients with coronary artery disease(CAD)after percutaneous coronary intervention(PCI).Methods:We recruited patients with CAD undergoing optical coherence tomography(OCT)-directed PCI between January 2019 and June 2021 for our single-center,hospital-based,retrospective cohort investigation.We assessed the link between post-PCI OFR and major adverse cardiovascular events(MACE)via multivariate Cox regression analy-sis.Results:Receiver operating characteristic analysis revealed that the best post-PCI OFR threshold for MACE was 0.91,and introduction of OFR into the baseline profile and OCT results markedly enhanced MACE identification after PCI.On the basis of survival curves,patients with OFR≤0.91(P<0.001)and thin-cap fibroatheroma(TCFA)(P=0.007)exhibited higher MACE incidence,and myocardial infarction(MI)incidence was considerably greater among patients with OFR≤0.91(P<0.001),compared with OFR>0.91.Multivariate Cox regression analysis suggested that OFR≤0.91(hazard ratio[HR]:3.60;95%confidence interval[CI]:1.24–10.44;P=0.019),and TCFA(HR:3.63;95%CI:1.42–9.20;P=0.007)were independent risk factors for MACE,and OFR≤0.91 was independently associated with MI(HR:14.64;95%CI:3.27–65.54;P<0.001).Conclusion:OFR after PCI is an independent MACE bio-indicator among patients with CAD.Adding OFR to post-PCI OCT results may potentially enhance MACE prediction.
文摘Using traditional particle tracking velocimetry based on optical flow for measuring areas with large velocity gradient changes may cause oversmoothing,resulting in significant measurement errors.To address this problem,the traditional particle tracking velocimetry method based on an optical flow was improved.The level set segmentation algorithm was used to obtain the boundary contour of the region with large velocity gradient changes,and the non-uniform flow field was divided into regions according to the boundary contour to obtain sub-regions with uniform velocity distribution.The particle tracking velocimetry method based on optical flow was used to measure the granular flow velocity in each sub-region,thus avoiding the problem of granular flow distribution.The simulation results show that the measurement accuracy of this method is approximately 10%higher than that of traditional methods.The method was applied to a velocity measurement experiment on dense granular flow in silos,and the velocity distribution of the granular flow was obtained,verifying the practicality of the method in granular flow fields.
文摘Current deformation measurement techniques suffer from limited spatial resolution. In this work, a highly accurate and high-resolution Horn Schunck optical flow method is developed and then applied to measuring the static deformation of a birdlike flexible airfoil at a series of angles of attack at Reynolds number 100,000 in a low speed, low noise wind tunnel. To allow relatively large displacements, a nonlinear Horn-Schunck model and a coarse-to-fine warping process are adopted. To preserve optical flow discontinuities, a nonquadratic penalization function, a multi- cue driven bilateral filtering and a principle component analysis of local image patterns are used. First, the accuracy and convergence of this Horn-Schunck technique are verified on a benchmark. Then, the maximum displacement that can be reliably calculated by this technique is studied on synthetic images. Both studies are compared with the performance of a Lucas-Kanade optical flow method. Finally, the Horn-Schunck technique is used to estimate the 3-D deformation of the birdlike airfoil through a stereoscopic camera setup. The results are compared with those computed by Lucas-Kanade optical flow, image correlation and numerical simulation.
基金This work was supported in part by the National Natural Science Foundation of China(Nos.61803025,62073031)the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)(No.FRF-IDRY-19010)the Beijing Top Discipline for Artificial Intelligent Science and Engineering,University of Science and Technology Beijing.
文摘The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Farneback algorithm is used to calculate the optical flow field of the first-view video frames taken by the on-board image transmission camera.Based on the optical flow information,a fuzzy obstacle avoidance controller is then designed to generate the FWAV steering commands.Experimental results show that the proposed obstacle avoidance method can accurately identify obstacles and achieve obstacle avoidance for FWAVs.
基金supported by the Armament Research Fund of China (No.9020A02010313BQ01)
文摘This paper focuses mainly on semi-strapdown image homing guided （SSIHG） system design based on optical flow for a six-degree-of-freedom （6-DOF） axial-symmetric skid-to-turn missile. Three optical flow algorithms suitable for large displacements are introduced and compared. The influence of different displacements on computational accuracy of the three algorithms is analyzed statistically. The total optical flow of the SSIHG missile is obtained using the Scale Invariant Feature Transform （SIFT） algorithm, which is the best among the three for large displacements. After removing the rotational optical flow caused by rotation of the gimbal and missile body from the total optical flow, the remaining translational optical flow is smoothed via Kalman filtering. The circular navigation guidance （CNG） law with impact angle constraint is then obtained utilizing the smoothed translational optical flow and position of the target image. Simulations are carried out under both disturbed and undisturbed conditions, and results indicate the proposed guidance strategy for SSIHG missiles can result in a precise target hit with a desired impact angle without the need for the time-to-go parameter.
基金Project(2012CB720003)supported by the National Basic Research Program of ChinaProjects(61320106010,61127007,61121003,61573019)supported by the National Natural Science Foundation of ChinaProject(2013DFE13040)supported by the Special Program for International Science and Technology Cooperation from Ministry of Science and Technology of China
文摘Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.
文摘A modification of Horn and Schunk＇s approach is investigated, which leads to a better preservation of flow discontinuities. It improves Horn-Schunk model in three aspects： （1） It replaces the smooth weight coefficient in the energy equation by the variable weight coefficient. （2） It adopts a novel method to compute the mean velocity. The novel method also reflects the effect of the intensity difference on the image velocity diffusion. （3） It introduces a more efficient iterative method than the Gauss-Seidel method to solve the associated Euler-Lagrange equation. The experiment results validate the better effect of the improved method on preserving discontinuities.
基金Foundation item： Projects（60835005, 90820302） supported by the National Natural Science Foundation of China Project（2007CB311001） supported by the National Basic Research Program of China
文摘Globally exponential stability （which implies convergence and uniqueness） of their classical iterative algorithm is established using methods of heat equations and energy integral after embedding the discrete iteration into a continuous flow. The stability condition depends explicitly on smoothness of the image sequence, size of image domain, value of the regularization parameter, and finally discretization step. Specifically, as the discretization step approaches to zero, stability holds unconditionally. The analysis also clarifies relations among the iterative algorithm, the original variation formulation and the PDE system. The proper regularity of solution and natural images is briefly surveyed and discussed. Experimental results validate the theoretical claims both on convergence and exponential stability.
基金supported by the National Natural Science Foundation of China[Grant No.41771479]the National High-Resolution Earth Observation System(the Civil Part)[Grant No.50-H31D01-0508-13/15]the Japan Society for the Promotion of Science[Grant No.22H03573].
文摘Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.
基金The National Natural Science Foundation of China (No. 60675017) The National Basic Research Program (973) of China (No. 2006CB303103)
文摘A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.
