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DTSTAMP:20260114T163648Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T151500
DTEND;TZID=Australia/Melbourne:20231214T153000
UID:siggraphasia_SIGGRAPH Asia 2023_sess123_papers_256@linklings.com
SUMMARY:Interaction-Driven Active 3D Reconstruction with Object Interiors
DESCRIPTION:Zihao Yan, Fubao Su, Mingyang Wang, and Ruizhen Hu (Shenzhen U
 niversity); Hao Zhang (Simon Fraser University); and Hui Huang (Shenzhen U
 niversity)\n\nWe introduce an active 3D reconstruction method, which integ
 rates visual perception, robot-object interaction, and 3D scanning to reco
 ver both the exterior and interior geometries of a target 3D object. Unlik
 e other works in active vision which focus on optimizing camera viewpoints
  to better investigate the environment, the primary feature of our reconst
 ruction is an analysis of the interactability of various parts of the targ
 et object and the ensuing part manipulation by a robot to enable scanning 
 of occluded regions. As a result, an understanding of part articulations o
 f the target object is obtained on top of complete geometry acquisition. O
 ur method operates fully automatically by a Fetch robot with built-in RGBD
  sensors. It iterates between interaction analysis and interaction-driven 
 reconstruction, scanning and reconstructing detected moveable parts one at
  a time, where both the articulated part detection and mesh reconstruction
  are carried out by neural networks. In the final step, all the remaining,
  non-articulated parts, including all the interior structures that had bee
 n exposed by prior part manipulations and subsequently scanned, are recons
 tructed to complete the acquisition. We demonstrate the performance of our
  active reconstruction method via qualitative and quantitative evaluation,
  ablation studies, comparisons to alternatives, as well as experiments in 
 a real environment.\n\nRegistration Category: Full Access\n\nSession Chair
 : Sai-Kit Yeung (Hong Kong University of Science and Technology)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_256&sess=sess123
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