Hyperspectral Inverse Skinning

dc.contributor.authorLiu, Songrunen_US
dc.contributor.authorTan, Jianchaoen_US
dc.contributor.authorDeng, Zhigangen_US
dc.contributor.authorGingold, Yotamen_US
dc.contributor.editorBenes, Bedrich and Hauser, Helwigen_US
dc.date.accessioned2020-10-06T16:53:57Z
dc.date.available2020-10-06T16:53:57Z
dc.date.issued2020
dc.description.abstractIn example‐based inverse linear blend skinning (LBS), a collection of poses (e.g. animation frames) are given, and the goal is finding skinning weights and transformation matrices that closely reproduce the input. These poses may come from physical simulation, direct mesh editing, motion capture or another deformation rig. We provide a re‐formulation of inverse skinning as a problem in high‐dimensional Euclidean space. The transformation matrices applied to a vertex across all poses can be thought of as a point in high dimensions. We cast the inverse LBS problem as one of finding a tight‐fitting simplex around these points (a well‐studied problem in hyperspectral imaging). Although we do not observe transformation matrices directly, the 3D position of a vertex across all of its poses defines an affine subspace, or flat. We solve a ‘closest flat’ optimization problem to find points on these flats, and then compute a minimum‐volume enclosing simplex whose vertices are the transformation matrices and whose barycentric coordinates are the skinning weights. We are able to create LBS rigs with state‐of‐the‐art reconstruction error and state‐of‐the‐art compression ratios for mesh animation sequences. Our solution does not consider weight sparsity or the rigidity of recovered transformations. We include observations and insights into the closest flat problem. Its ideal solution and optimal LBS reconstruction error remain an open problem.en_US
dc.description.number6
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13903
dc.identifier.issn1467-8659
dc.identifier.pages49-65
dc.identifier.urihttps://doi.org/10.1111/cgf.13903
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13903
dc.publisher© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltden_US
dc.subjectlinear blend skinning
dc.subjectdeformation
dc.subjectanimation
dc.subjectaffine geometry
dc.subjecthyperspectral unmixing
dc.subject• Computing methodologies → Mesh geometry models
dc.subjectMotion processing
dc.titleHyperspectral Inverse Skinningen_US
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