Reconstruction of a fluttering flag from a single image

Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with v...
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Autor*in:	Tao Hu [verfasserIn] Jun Li [verfasserIn] Guihuan Guo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Übergeordnetes Werk:	In: Journal of Algorithms & Computational Technology - SAGE Publishing, 2017, 15(2021)
Übergeordnetes Werk:	volume:15 ; year:2021

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1177/1748302620983656

Katalog-ID:	DOAJ014932415

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allfields	10.1177/1748302620983656 doi (DE-627)DOAJ014932415 (DE-599)DOAJf20de72139f24f95ad5a4eca9154d3d9 DE-627 ger DE-627 rakwb eng T57-57.97 QA1-939 Tao Hu verfasserin aut Reconstruction of a fluttering flag from a single image 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image. Applied mathematics. Quantitative methods Mathematics Jun Li verfasserin aut Guihuan Guo verfasserin aut In Journal of Algorithms & Computational Technology SAGE Publishing, 2017 15(2021) (DE-627)591513978 (DE-600)2478205-1 17483026 nnns volume:15 year:2021 https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/article/f20de72139f24f95ad5a4eca9154d3d9 kostenfrei https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/toc/1748-3026 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2020 GBV_ILN_2034 GBV_ILN_2057 GBV_ILN_2068 GBV_ILN_2098 GBV_ILN_2706 GBV_ILN_2707 GBV_ILN_2890 GBV_ILN_2954 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021
spelling	10.1177/1748302620983656 doi (DE-627)DOAJ014932415 (DE-599)DOAJf20de72139f24f95ad5a4eca9154d3d9 DE-627 ger DE-627 rakwb eng T57-57.97 QA1-939 Tao Hu verfasserin aut Reconstruction of a fluttering flag from a single image 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image. Applied mathematics. Quantitative methods Mathematics Jun Li verfasserin aut Guihuan Guo verfasserin aut In Journal of Algorithms & Computational Technology SAGE Publishing, 2017 15(2021) (DE-627)591513978 (DE-600)2478205-1 17483026 nnns volume:15 year:2021 https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/article/f20de72139f24f95ad5a4eca9154d3d9 kostenfrei https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/toc/1748-3026 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2020 GBV_ILN_2034 GBV_ILN_2057 GBV_ILN_2068 GBV_ILN_2098 GBV_ILN_2706 GBV_ILN_2707 GBV_ILN_2890 GBV_ILN_2954 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021
allfields_unstemmed	10.1177/1748302620983656 doi (DE-627)DOAJ014932415 (DE-599)DOAJf20de72139f24f95ad5a4eca9154d3d9 DE-627 ger DE-627 rakwb eng T57-57.97 QA1-939 Tao Hu verfasserin aut Reconstruction of a fluttering flag from a single image 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image. Applied mathematics. Quantitative methods Mathematics Jun Li verfasserin aut Guihuan Guo verfasserin aut In Journal of Algorithms & Computational Technology SAGE Publishing, 2017 15(2021) (DE-627)591513978 (DE-600)2478205-1 17483026 nnns volume:15 year:2021 https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/article/f20de72139f24f95ad5a4eca9154d3d9 kostenfrei https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/toc/1748-3026 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2020 GBV_ILN_2034 GBV_ILN_2057 GBV_ILN_2068 GBV_ILN_2098 GBV_ILN_2706 GBV_ILN_2707 GBV_ILN_2890 GBV_ILN_2954 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021
allfieldsGer	10.1177/1748302620983656 doi (DE-627)DOAJ014932415 (DE-599)DOAJf20de72139f24f95ad5a4eca9154d3d9 DE-627 ger DE-627 rakwb eng T57-57.97 QA1-939 Tao Hu verfasserin aut Reconstruction of a fluttering flag from a single image 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image. Applied mathematics. Quantitative methods Mathematics Jun Li verfasserin aut Guihuan Guo verfasserin aut In Journal of Algorithms & Computational Technology SAGE Publishing, 2017 15(2021) (DE-627)591513978 (DE-600)2478205-1 17483026 nnns volume:15 year:2021 https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/article/f20de72139f24f95ad5a4eca9154d3d9 kostenfrei https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/toc/1748-3026 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2020 GBV_ILN_2034 GBV_ILN_2057 GBV_ILN_2068 GBV_ILN_2098 GBV_ILN_2706 GBV_ILN_2707 GBV_ILN_2890 GBV_ILN_2954 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021
allfieldsSound	10.1177/1748302620983656 doi (DE-627)DOAJ014932415 (DE-599)DOAJf20de72139f24f95ad5a4eca9154d3d9 DE-627 ger DE-627 rakwb eng T57-57.97 QA1-939 Tao Hu verfasserin aut Reconstruction of a fluttering flag from a single image 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image. Applied mathematics. Quantitative methods Mathematics Jun Li verfasserin aut Guihuan Guo verfasserin aut In Journal of Algorithms & Computational Technology SAGE Publishing, 2017 15(2021) (DE-627)591513978 (DE-600)2478205-1 17483026 nnns volume:15 year:2021 https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/article/f20de72139f24f95ad5a4eca9154d3d9 kostenfrei https://doi.org/10.1177/1748302620983656 kostenfrei https://doaj.org/toc/1748-3026 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2020 GBV_ILN_2034 GBV_ILN_2057 GBV_ILN_2068 GBV_ILN_2098 GBV_ILN_2706 GBV_ILN_2707 GBV_ILN_2890 GBV_ILN_2954 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021
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callnumber-first	T - Technology
author	Tao Hu
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title_sort	reconstruction of a fluttering flag from a single image
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title_auth	Reconstruction of a fluttering flag from a single image
abstract	Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image.
abstractGer	Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image.
abstract_unstemmed	Reconstructing a 3 D object from a single image is a challenging task because determining useful geometric structure information from a single image is difficult. In this paper, we propose a novel method to extract the 3 D mesh of a flag from a single image and drive the flag model to flutter with virtual wind. A deep convolutional neural fields model is first used to generate a depth map of a single image. Based on the Alpha Shape, a coarse 2 D mesh of flag is reconstructed by sampling at different depth regions. Then, we optimize the mesh to generate a mesh with depth based on Restricted Frontal-Delaunay. We transform the Delaunay mesh with depth into a simple spring model and use a velocity-based solver to calculate the moving position of the virtual flag model. The experiments demonstrate that the proposed method can construct a realistic fluttering flag video from a single image.
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title_short	Reconstruction of a fluttering flag from a single image
url	https://doi.org/10.1177/1748302620983656 https://doaj.org/article/f20de72139f24f95ad5a4eca9154d3d9 https://doaj.org/toc/1748-3026
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up_date	2024-07-04T01:01:17.013Z
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