4D Reconstruction of Blooming Flowers

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dc.contributor.authorZheng, Qianen_US
dc.contributor.authorFan, Xiaochenen_US
dc.contributor.authorGong, Minglunen_US
dc.contributor.authorSharf, Andreien_US
dc.contributor.authorDeussen, Oliveren_US
dc.contributor.authorHuang, Huien_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2018-01-10T07:36:38Z
dc.date.available2018-01-10T07:36:38Z
dc.date.issued2017
dc.description.abstractFlower blooming is a beautiful phenomenon in nature as flowers open in an intricate and complex manner whereas petals bend, stretch and twist under various deformations. Flower petals are typically thin structures arranged in tight configurations with heavy self‐occlusions. Thus, capturing and reconstructing spatially and temporally coherent sequences of blooming flowers is highly challenging. Early in the process only exterior petals are visible and thus interior parts will be completely missing in the captured data. Utilizing commercially available 3D scanners, we capture the visible parts of blooming flowers into a sequence of 3D point clouds. We reconstruct the flower geometry and deformation over time using a template‐based dynamic tracking algorithm. To track and model interior petals hidden in early stages of the blooming process, we employ an adaptively constrained optimization. Flower characteristics are exploited to track petals both forward and backward in time. Our methods allow us to faithfully reconstruct the flower blooming process of different species. In addition, we provide comparisons with state‐of‐the‐art physical simulation‐based approaches and evaluate our approach by using photos of captured real flowers.Flower blooming is a beautiful phenomenon in nature as flowers open in an intricate and complex manner whereas petals bend, stretch and twist under various deformations. Flower petals are typically thin structures arranged in tight configurations with heavy self‐occlusions. Thus, capturing and reconstructing spatially and temporally coherent sequences of blooming flowers is highly challenging. Early in the process only exterior petals are visible and thus interior parts will be completely missing in the captured data. Utilizing commercially available 3D scanners, we capture the visible parts of blooming flowers into a sequence of 3D point clouds. We reconstruct the flower geometry and deformation over time using a template‐based dynamic tracking algorithm. To track and model interior petals hidden in early stages of the blooming process, we employ an adaptively constrained optimization. Flower characteristics are exploited to track petals both forward and backward in time. Our methods allow us to faithfully reconstruct the flower blooming process of different species.en_US
dc.description.number6
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.12989
dc.identifier.issn1467-8659
dc.identifier.pages405-417
dc.identifier.urihttps://doi.org/10.1111/cgf.12989
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf12989
dc.publisher© 2017 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectgeometric modelling
dc.subjectmodelling
dc.subjectbehavioural animation
dc.subjectanimation
dc.subjectpoint‐based animation
dc.subjectanimation
dc.subjectI.3.5 [Computer Graphics]: Computational Geometry and Object Modelling Modelling; I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism Animation
dc.title4D Reconstruction of Blooming Flowersen_US
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