Starting from the traditional form of“graphic”architectural education,this paper explores a teaching method of entity construction experience,instrument assistance,and digital virtual expression symbiosis symbiosis ...Starting from the traditional form of“graphic”architectural education,this paper explores a teaching method of entity construction experience,instrument assistance,and digital virtual expression symbiosis symbiosis from three aspects:environmental perception,ontology perception,and extension perception.Using physical perception as a medium,and gradually rising from active perception to a comprehensive expression of visual audience perception through practical operation,it allows students to have a more comprehensive understanding of the meaning of architectural design on the basis of the“graphic”expression paradigm.展开更多
This paper focuses on the application of interactive media technology in the visual interpretation of traditional graphic urban public spaces in China.Case studies and practical exploration show that interactive media...This paper focuses on the application of interactive media technology in the visual interpretation of traditional graphic urban public spaces in China.Case studies and practical exploration show that interactive media technologies such as projection mapping,interactive devices,virtual reality technology,etc.,have realized the diversity of traditional graphics display forms in urban public space.The rich interactive experience design enhances the sense of participation and experience of urban citizens and tourists and promotes the visual culture transmission of traditional Chinese graphics.The future urban public space exhibition is destined to continue to deepen the integration of technology and graphics,promote the visual communication of traditional Chinese graphics visual interpretation in urban public space,and promote sustainable innovation in cultural output in urban public space exhibitions around the world.展开更多
To reduce the computing time of composite computer-generated holograms （CGHs） gen- eration based upon the angular projection algorithm for holographic three-dimensional （3D） display, a grid-based holographic displ...To reduce the computing time of composite computer-generated holograms （CGHs） gen- eration based upon the angular projection algorithm for holographic three-dimensional （3D） display, a grid-based holographic display （ GHD ） scheme was designed. The grid computing technology was applied to numerically process the different angular projections of an object in distributed-parallel manner to create the corresponding CGHs. The whole treatment of a projection was regarded as a job executed on the grid node machine. The number of jobs which were submitted to grid nodes, therefore, was equal to that of the projections of the object. A Condor-based grid testbed was constructed to verify the feasibility of the GHD scheme, and a graphical user interface （GUI） program and several service modules were developed for it. A 3D terrain model as an example was processed on the testbed. The result showed that the scheme was feasible and able to improve the execution elficiency greatly.展开更多
Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training dataset...Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization.The model-driven deep learning introduces the diffraction model into the neural network.It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation.However,the existing model-driven deep learning algorithms face the problem of insufficient constraints.In this study,we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation,called 4K Diffraction Model-driven Network(4K-DMDNet).The constraint of the reconstructed images in the frequency domain is strengthened.And a network structure that combines the residual method and sub-pixel convolution method is built,which effectively enhances the fitting ability of the network for inverse problems.The generalization of the 4K-DMDNet is demonstrated with binary,grayscale and 3D images.High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm,520 nm,and 638 nm.展开更多
This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees wi...This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees with that of numerical analysis in terms of the lattice parameters of austenite and martensite and shear mechanism supposed in Fe-22%Ni-0.8%C alloy, so does orientation relationships.展开更多
Currently,some photorealistic computer graphics are very similar to photographic images.Photorealistic computer generated graphics can be forged as photographic images,causing serious security problems.The aim of this...Currently,some photorealistic computer graphics are very similar to photographic images.Photorealistic computer generated graphics can be forged as photographic images,causing serious security problems.The aim of this work is to use a deep neural network to detect photographic images(PI)versus computer generated graphics(CG).In existing approaches,image feature classification is computationally intensive and fails to achieve realtime analysis.This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks(DCNNs).Compared with some existing methods,the proposed method achieves real-time forensic tasks by deepening the network structure.Experimental results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.展开更多
As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it ma...As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it may lead to potential social,legal or private consequences.To this end,it is very necessary and also challenging to find effective methods to differentiate between them.In this paper,a novel leading digit law,also called Benford's law,based method to identify computer graphics is proposed.More specifically,statistics of the most significant digits are extracted from image's Discrete Cosine Transform(DCT) coefficients and magnitudes of image's gradient,and then the Support Vector Machine(SVM) based classifiers are built.Results of experiments on the image datasets indicate that the proposed method is comparable to prior works.Besides,it possesses low dimensional features and low computational complexity.展开更多
基金(2021jyxm0419,2022jyxm450,2021kcszsfkc137)Anhui Provincial Key Laboratory of Huizhou Architecture Open Subjects Funding Project(HPJZ-2020-03)Anhui Agricultural University Quality Engineering Project(2021auxsxxkc17,2021aujyxm59).
文摘Starting from the traditional form of“graphic”architectural education,this paper explores a teaching method of entity construction experience,instrument assistance,and digital virtual expression symbiosis symbiosis from three aspects:environmental perception,ontology perception,and extension perception.Using physical perception as a medium,and gradually rising from active perception to a comprehensive expression of visual audience perception through practical operation,it allows students to have a more comprehensive understanding of the meaning of architectural design on the basis of the“graphic”expression paradigm.
文摘This paper focuses on the application of interactive media technology in the visual interpretation of traditional graphic urban public spaces in China.Case studies and practical exploration show that interactive media technologies such as projection mapping,interactive devices,virtual reality technology,etc.,have realized the diversity of traditional graphics display forms in urban public space.The rich interactive experience design enhances the sense of participation and experience of urban citizens and tourists and promotes the visual culture transmission of traditional Chinese graphics.The future urban public space exhibition is destined to continue to deepen the integration of technology and graphics,promote the visual communication of traditional Chinese graphics visual interpretation in urban public space,and promote sustainable innovation in cultural output in urban public space exhibitions around the world.
文摘To reduce the computing time of composite computer-generated holograms （CGHs） gen- eration based upon the angular projection algorithm for holographic three-dimensional （3D） display, a grid-based holographic display （ GHD ） scheme was designed. The grid computing technology was applied to numerically process the different angular projections of an object in distributed-parallel manner to create the corresponding CGHs. The whole treatment of a projection was regarded as a job executed on the grid node machine. The number of jobs which were submitted to grid nodes, therefore, was equal to that of the projections of the object. A Condor-based grid testbed was constructed to verify the feasibility of the GHD scheme, and a graphical user interface （GUI） program and several service modules were developed for it. A 3D terrain model as an example was processed on the testbed. The result showed that the scheme was feasible and able to improve the execution elficiency greatly.
基金We are grateful for financial supports from National Natural Science Foundation of China(62035003,61775117)China Postdoctoral Science Foundation(BX2021140)Tsinghua University Initiative Scientific Research Program(20193080075).
文摘Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization.The model-driven deep learning introduces the diffraction model into the neural network.It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation.However,the existing model-driven deep learning algorithms face the problem of insufficient constraints.In this study,we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation,called 4K Diffraction Model-driven Network(4K-DMDNet).The constraint of the reconstructed images in the frequency domain is strengthened.And a network structure that combines the residual method and sub-pixel convolution method is built,which effectively enhances the fitting ability of the network for inverse problems.The generalization of the 4K-DMDNet is demonstrated with binary,grayscale and 3D images.High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm,520 nm,and 638 nm.
文摘This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees with that of numerical analysis in terms of the lattice parameters of austenite and martensite and shear mechanism supposed in Fe-22%Ni-0.8%C alloy, so does orientation relationships.
基金This work is supported,in part,by the National Natural Science Foundation of China under grant numbers U1536206,U1405254,61772283,61602253,61672294,61502242In part,by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20150925 and BK20151530+1 种基金In part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fundIn part,by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.
文摘Currently,some photorealistic computer graphics are very similar to photographic images.Photorealistic computer generated graphics can be forged as photographic images,causing serious security problems.The aim of this work is to use a deep neural network to detect photographic images(PI)versus computer generated graphics(CG).In existing approaches,image feature classification is computationally intensive and fails to achieve realtime analysis.This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks(DCNNs).Compared with some existing methods,the proposed method achieves real-time forensic tasks by deepening the network structure.Experimental results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.
文摘As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it may lead to potential social,legal or private consequences.To this end,it is very necessary and also challenging to find effective methods to differentiate between them.In this paper,a novel leading digit law,also called Benford's law,based method to identify computer graphics is proposed.More specifically,statistics of the most significant digits are extracted from image's Discrete Cosine Transform(DCT) coefficients and magnitudes of image's gradient,and then the Support Vector Machine(SVM) based classifiers are built.Results of experiments on the image datasets indicate that the proposed method is comparable to prior works.Besides,it possesses low dimensional features and low computational complexity.
