To speed up the reconstruction of 3D dynamic scenes in an ordinary hardware platform, we propose an efficient framework to reconstruct 3D dynamic objects using a multiscale-contour-based interpolation from multi-view ...To speed up the reconstruction of 3D dynamic scenes in an ordinary hardware platform, we propose an efficient framework to reconstruct 3D dynamic objects using a multiscale-contour-based interpolation from multi-view videos. Our framework takes full advantage of spatio-temporal-contour consistency. It exploits the property to interpolate single contours, two neighboring contours which belong to the same model, and two contours which belong to the same view at different times, corresponding to point-, contour-, and model-level interpolations, respectively. The framework formulates the interpolation of two models as point cloud transport rather than non-rigid surface deformation. Our framework speeds up the reconstruction of a dynamic scene while improving the accuracy of point-pairing which is used to perform the interpolation. We obtain a higher frame rate, spatio-temporal-coherence, and a quasi-dense point cloud sequence with color information. Experiments with real data were conducted to test the efficiency of the framework.展开更多
Under the perspective projection assumption,non-Lambertian photometric stereo is a highly non-linear problem.In this study,we present an optimized framework for reconstructing the surface normal and depth with non-Lam...Under the perspective projection assumption,non-Lambertian photometric stereo is a highly non-linear problem.In this study,we present an optimized framework for reconstructing the surface normal and depth with non-Lambertian reflection models under perspective projection.By decomposing the images into diffuse and specular components,we compute the surface normal and reflectance simultaneously.We also propose a variational formulation that is robust and useful for surface reconstruction.The experiments show that our method accurately reconstructs both the surface shape and reflectance of colorful objects with non-Lambertian surfaces.展开更多
Generally,the distributed bundle adjustment(DBA)method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer.However,the p...Generally,the distributed bundle adjustment(DBA)method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer.However,the performance considerably degrades owing to the overhead introduced by the additional block partitioning step and synchronous waiting.Therefore,we propose a low-overhead consensus framework.A partial barrier based asynchronous method is proposed to early achieve consensus with respect to the faster worker nodes to avoid waiting for the slower ones.A scene summarization procedure is designed and integrated into the block partitioning step to ensure that clustering can be performed on the small summarized scene.Experiments conducted on public datasets show that our method can improve the worker node utilization rate and reduce the block partitioning time.Also,sample applications are demonstrated using our large-scale culture heritage datasets.展开更多
基金Project supported by the National Basic Research Program(973)of China(No.2012CB725305)the Natural Science Foundation of Guizhou Province,China(No.20132094)+1 种基金the National Social Science Fund,China(No.12&ZD32)the Introducing Talents Foundation of Guizhou University,China(No.2012028)
文摘To speed up the reconstruction of 3D dynamic scenes in an ordinary hardware platform, we propose an efficient framework to reconstruct 3D dynamic objects using a multiscale-contour-based interpolation from multi-view videos. Our framework takes full advantage of spatio-temporal-contour consistency. It exploits the property to interpolate single contours, two neighboring contours which belong to the same model, and two contours which belong to the same view at different times, corresponding to point-, contour-, and model-level interpolations, respectively. The framework formulates the interpolation of two models as point cloud transport rather than non-rigid surface deformation. Our framework speeds up the reconstruction of a dynamic scene while improving the accuracy of point-pairing which is used to perform the interpolation. We obtain a higher frame rate, spatio-temporal-coherence, and a quasi-dense point cloud sequence with color information. Experiments with real data were conducted to test the efficiency of the framework.
基金the Technological Program of Cultural Relics Preservation of Zhejiang Province,Chinathe Key Research and Development Program of Zhejiang Province,China(No.2018C03051)the National Standard Development Program of Cultural Relics Protection of China(No.581250-T0170B)。
文摘Under the perspective projection assumption,non-Lambertian photometric stereo is a highly non-linear problem.In this study,we present an optimized framework for reconstructing the surface normal and depth with non-Lambertian reflection models under perspective projection.By decomposing the images into diffuse and specular components,we compute the surface normal and reflectance simultaneously.We also propose a variational formulation that is robust and useful for surface reconstruction.The experiments show that our method accurately reconstructs both the surface shape and reflectance of colorful objects with non-Lambertian surfaces.
基金Project supported by the Key R&D Program of Zhejiang Province,China(No.2018C03051)the Key Scientific Research Base for Digital Conservation of Cave Temples of the National Cultural Heritage Administration,China。
文摘Generally,the distributed bundle adjustment(DBA)method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer.However,the performance considerably degrades owing to the overhead introduced by the additional block partitioning step and synchronous waiting.Therefore,we propose a low-overhead consensus framework.A partial barrier based asynchronous method is proposed to early achieve consensus with respect to the faster worker nodes to avoid waiting for the slower ones.A scene summarization procedure is designed and integrated into the block partitioning step to ensure that clustering can be performed on the small summarized scene.Experiments conducted on public datasets show that our method can improve the worker node utilization rate and reduce the block partitioning time.Also,sample applications are demonstrated using our large-scale culture heritage datasets.
