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TZID:Australia/Brisbane
X-LIC-LOCATION:Australia/Brisbane
BEGIN:STANDARD
DTSTART:19920301T030000
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
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BEGIN:VEVENT
DTSTAMP:20191203T080637Z
LOCATION:Great Hall 1&2
DTSTART;TZID=Australia/Brisbane:20191117T191100
DTEND;TZID=Australia/Brisbane:20191117T191200
UID:siggraphasia_SIGGRAPH Asia 2019_sess222_papers_272@linklings.com
SUMMARY:DReCon: Data-Driven Responsive Control of Physics-Based Characters
DESCRIPTION:Technical Papers Fast-Forward \n\nDReCon: Data-Driven Responsi
 ve Control of Physics-Based Characters\n\nBergamin, Clavet, Holden, Forbes
 \n\nInteractive control of self-balancing, physically simulated humanoids 
 is a long standing problem in the field of real-time character animation. 
 While physical simulation guarantees realistic interactions in the virtual
  world, simulated characters can appear unnatural if they perform unusual 
 movements in order to maintain balance. Therefore, obtaining a high level 
 of responsiveness to user control, runtime performance, and diversity has 
 often been overlooked in exchange for motion quality. Recent work in the f
 ield of deep reinforcement learning has shown that training physically sim
 ulated characters to follow motion capture clips can yield high quality tr
 acking results. We propose a two-step approach for building responsive sim
 ulated character controllers from unstructured motion capture data. First,
  meaningful features from the data such as movement direction, heading dir
 ection, speed, and locomotion style, are interactively specified and drive
  a kinematic character controller implemented using motion matching. Secon
 d, reinforcement learning is used to train a simulated character controlle
 r that is general enough to track the entire distribution of motion that c
 an be generated by the kinematic controller. Our design emphasizes respons
 iveness to user input, visual quality, and low runtime cost for applicatio
 n in video-games.\n\nRegistration Category: Platinum Pass, Full Conference
  Pass, Full Conference One-Day Pass, Basic Conference Pass, Student One-Da
 y Pass, Exhibitor Pass
URL:https://sa2019.conference-program.com/presentation?id=papers_272&sess=
 sess222
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