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DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20230103T035309Z
LOCATION:Room 324\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221207T170000
DTEND;TZID=Asia/Seoul:20221207T183000
UID:siggraphasia_SIGGRAPH Asia 2022_sess175_papers_360@linklings.com
SUMMARY:Simulation of Hand Anatomy Using Medical Imaging
DESCRIPTION:Technical Papers, TOG\n\nSimulation of Hand Anatomy Using Medi
 cal Imaging\n\nZheng, Wang, Huang, Barbic\n\nPrecision modeling of the han
 d internal 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 an
 d cannot be predicted merely from the anatomy in a single pose. We give a 
 method to simulate the volumetric shape of hand's musculoskeletal organs t
 o any pose in the hand's range of motion, producing external hand shapes a
 nd internal organ shapes that match ground truth optical scans and medical
  images (MRI) in multiple scanned poses. We achieve this by combining MRI 
 images in multiple hand poses with FEM multibody nonlinear elastoplastic s
 imulation. Our system models bones, muscles, tendons, joint ligaments and 
 fat as separate volumetric organs that mechanically interact through conta
 ct and attachments, and whose shape matches medical images (MRI) in the MR
 I-scanned hand poses. The match to MRI is achieved by incorporating pose-s
 pace deformation and plastic strains into the simulation. We show how to d
 o this in a non-intrusive manner that still retains all the simulation ben
 efits, namely the ability to prescribe realistic material properties, gene
 ralize to arbitrary poses, preserve volume and obey contacts and attachmen
 ts. We use our method to produce volumetric renders of the internal anatom
 y 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 sc
 ans, and demonstrated that we qualitatively and quantitatively substantial
 ly decreased the error compared to previous work. We tested our method on 
 five complex hand sequences, generated both using keyframe animation and p
 erformance animation using modern hand tracking techniques.\n\nRegistratio
 n Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: 
 IN-PERSON, ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_360&sess=sess17
 5
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