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DTSTAMP:20240214T070248Z
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:Technical Communications, Technical Papers, TOG\n\nZihao Yan, 
 Fubao Su, Mingyang Wang, and Ruizhen Hu (Shenzhen University); Hao Zhang (
 Simon Fraser University); and Hui Huang (Shenzhen University)\n\nWe introd
 uce an active 3D reconstruction method, which integrates visual perception
 , robot-object interaction, and 3D scanning to recover both the exterior a
 nd interior geometries of a target 3D object. Unlike other works in active
  vision which focus on optimizing camera viewpoints to better investigate 
 the environment, the primary feature of our reconstruction is an analysis 
 of the interactability of various parts of the target object and the ensui
 ng part manipulation by a robot to enable scanning of occluded regions. As
  a result, an understanding of part articulations of the target object is 
 obtained on top of complete geometry acquisition. Our method operates full
 y automatically by a Fetch robot with built-in RGBD sensors. It iterates b
 etween interaction analysis and interaction-driven reconstruction, scannin
 g and reconstructing detected moveable parts one at a time, where both the
  articulated part detection and mesh reconstruction are carried out by neu
 ral networks. In the final step, all the remaining, non-articulated parts,
  including all the interior structures that had been exposed by prior part
  manipulations and subsequently scanned, are reconstructed to complete the
  acquisition. We demonstrate the performance of our active reconstruction 
 method via qualitative and quantitative evaluation, ablation studies, comp
 arisons to alternatives, as well as experiments in a real environment.\n\n
 Registration Category: Full Access\n\nSession Chair: Sai-Kit Yeung (Hong K
 ong University of Science and Technology)
URL:https://asia.siggraph.org/2023/full-program?id=papers_256&sess=sess123
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