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DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20230103T035307Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_360@linklings.com
SUMMARY:Simulation of Hand Anatomy Using Medical Imaging
DESCRIPTION:Technical Papers\n\nSimulation of Hand Anatomy Using Medical I
 maging\n\nZheng, Wang, Huang, Barbic\n\nPrecision modeling of the hand int
 ernal musculoskeletal anatomy has been largely limited to individual poses
 , and has not been connected into continuous volumetric motion of the hand
  anatomy actuating across the hand's entire range of motion. This is for a
  good reason, as hand anatomy and its motion are extremely complex and can
 not be predicted merely from the anatomy in a single pose. We give a metho
 d to simulate the volumetric shape of hand's musculoskeletal organs to any
  pose in the hand's range of motion, producing external hand shapes and in
 ternal organ shapes that match ground truth optical scans and medical imag
 es (MRI) in multiple scanned poses. We achieve this by combining MRI image
 s in multiple hand poses with FEM multibody nonlinear elastoplastic simula
 tion. Our system models bones, muscles, tendons, joint ligaments and fat a
 s separate volumetric organs that mechanically interact through contact an
 d attachments, and whose shape matches medical images (MRI) in the MRI-sca
 nned hand poses. The match to MRI is achieved by incorporating pose-space 
 deformation and plastic strains into the simulation. We show how to do thi
 s in a non-intrusive manner that still retains all the simulation benefits
 , namely the ability to prescribe realistic material properties, generaliz
 e to arbitrary poses, preserve volume and obey contacts and attachments. W
 e use our method to produce volumetric renders of the internal anatomy of 
 the human hand in motion, and to compute and render highly realistic hand 
 surface shapes. We evaluated our method by comparing it to optical scans, 
 and demonstrated that we qualitatively and quantitatively substantially de
 creased the error compared to previous work. We tested our method on five 
 complex hand sequences, generated both using keyframe animation and perfor
 mance animation using modern hand tracking techniques.\n\nRegistration Cat
 egory: FULL ACCESS, EXPERIENCE PLUS ACCESS, EXPERIENCE ACCESS, TRADE EXHIB
 ITOR\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_360&sess=sess15
 3
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