A 3D surface reconstruction method using a binocular stereo vision technology and a coded structured light,which combines a gray code with phase-shift has been studied.The accuracy of the 3 D surface reconstruction ma...A 3D surface reconstruction method using a binocular stereo vision technology and a coded structured light,which combines a gray code with phase-shift has been studied.The accuracy of the 3 D surface reconstruction mainly depends on the decoding of gray code views and phase-shift views.In order to find the boundary accurately,gray code patterns and their inverses are projected onto a human eye plaster model.The period dislocation between the gray code views and the phase-shift views in the course of decoding has been analyzed and a new method has been proposed to solve it.The splicing method is based on feature points.The result of the 3D surface reconstruction shows the accuracy and reliability of our method.展开更多
3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective.When existing methods reconstruct the mesh surface of complex objects,the surface details are difficult ...3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective.When existing methods reconstruct the mesh surface of complex objects,the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework;the 3D topology is easily limited by predefined templates and inflexible,and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology,thus destroying the surface details;the training of the reconstruction network is limited by the large amount of information attached to the mesh vertices,and the training time of the reconstructed network is too long.In this paper,we propose a method for fast mesh reconstruction from single view based on Graph Convolutional Network(GCN)and topology modification.We use GCN to ensure the generation of high-quality mesh surfaces and use topology modification to improve the flexibility of the topology.Meanwhile,a feature fusion method is proposed to make full use of the features of each stage of the image hierarchically.We use 3D open dataset ShapeNet to train our network and add a new weight parameter to speed up the training process.Extensive experiments demonstrate that our method can not only reconstruct object meshes on complex topological surfaces,but also has better qualitative and quantitative results.展开更多
Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sen...Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.展开更多
文摘A 3D surface reconstruction method using a binocular stereo vision technology and a coded structured light,which combines a gray code with phase-shift has been studied.The accuracy of the 3 D surface reconstruction mainly depends on the decoding of gray code views and phase-shift views.In order to find the boundary accurately,gray code patterns and their inverses are projected onto a human eye plaster model.The period dislocation between the gray code views and the phase-shift views in the course of decoding has been analyzed and a new method has been proposed to solve it.The splicing method is based on feature points.The result of the 3D surface reconstruction shows the accuracy and reliability of our method.
基金This work was supported,in part,by the Natural Science Foundation of Jiangsu Province under Grant Numbers BK20201136,BK20191401in part,by the National Nature Science Foundation of China under Grant Numbers 61502240,61502096,61304205,61773219in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective.When existing methods reconstruct the mesh surface of complex objects,the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework;the 3D topology is easily limited by predefined templates and inflexible,and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology,thus destroying the surface details;the training of the reconstruction network is limited by the large amount of information attached to the mesh vertices,and the training time of the reconstructed network is too long.In this paper,we propose a method for fast mesh reconstruction from single view based on Graph Convolutional Network(GCN)and topology modification.We use GCN to ensure the generation of high-quality mesh surfaces and use topology modification to improve the flexibility of the topology.Meanwhile,a feature fusion method is proposed to make full use of the features of each stage of the image hierarchically.We use 3D open dataset ShapeNet to train our network and add a new weight parameter to speed up the training process.Extensive experiments demonstrate that our method can not only reconstruct object meshes on complex topological surfaces,but also has better qualitative and quantitative results.
基金supported by the National Natural Science Foundation of China(Grant No.52402430,52572380)the Natural Science Foundation of Shanghai(Grant No.23ZR1466300).
文摘Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.
