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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035312Z
LOCATION:Room 324\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221209T090000
DTEND;TZID=Asia/Seoul:20221209T103000
UID:siggraphasia_SIGGRAPH Asia 2022_sess172_papers_501@linklings.com
SUMMARY:Isometric Energies for Recovering Injectivity in Constrained Mappi
 ng
DESCRIPTION:Technical Communications, Technical Papers\n\nIsometric Energi
 es for Recovering Injectivity in Constrained Mapping\n\nDu, Kaufman, Zhou,
  Kovalsky, Yan...\n\nComputing injective maps with low distortions is a lo
 ng-standing problem in computer graphics. Such maps are particularly chall
 enging to obtain in the presence of positional constraints, because an inj
 ective initial map is often not available. Recently, several energies were
  proposed and shown to be highly successful in optimizing injectivity from
  non-injective initial maps while satisfying positional constraints. Howev
 er, minimizing these energies tends to produce elements with significant i
 sometric distortions. This paper presents simple variants of these energie
 s that retain their desirable traits while promoting isometry. While our m
 ethod is not guaranteed to provide an injective map, we observe that, on l
 arge-scale 2D and 3D data sets, minimizing the proposed isometric variants
  results in a similar level of success in recovering injectivity as the or
 iginal energies but a significantly lower isometric distortion.\n\nRegistr
 ation Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nForm
 at: IN-PERSON, ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_501&sess=sess17
 2
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