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Real-time visual hull computation based on GPU

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A real time visual hull parallel computation method is proposed based on GPU. Firstly, an effective Octree data structure is built on GPU, which establishes the correspondence between voxels and the thread ID of CUDA. Secondly, for large-scale parallel data in the projection test of visual hull calculation, the convex hull of the projected vertices is accelerated to use the GPU programmable features. Finally, the redundant edge computation in marching cubes algorithm is reduced by building the edge lookup table. Then, parallel streaming data reduction based on prefix-sum excludes empty voxels from the lookup table, which can improve the computation effectively. Experimental results show that, for large-scale data, accurate visual hull can be efficiently reconstructed by the proposed algorithm on a common PC and GPU platform.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1792-1797
Number of pages6
ISBN (Electronic)9781467396745
DOIs
StatePublished - 2015
Externally publishedYes
EventIEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015 - Zhuhai, China
Duration: 6 Dec 20159 Dec 2015

Publication series

Name2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015

Conference

ConferenceIEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015
Country/TerritoryChina
CityZhuhai
Period6/12/159/12/15

Keywords

  • GPGPU
  • Marching Cubes
  • Octree
  • Visual Hull

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