GPU-based Scalable Volumetric Reconstruction for Multi-view Stereo

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We present a new scalable volumetric reconstruction algorithm for multi-view stereo using a graphics processing unit (GPU). It is an effectively parallelized GPU algorithm that simultaneously uses a large number of GPU threads, each of which performs voxel carving, in order to integrate depth maps with images from multiple views. Each depth map, triangulated from pair-wise semi-dense correspondences, represents a view-dependent surface of the scene. This algorithm also provides scalability for large-scale scene reconstruction in a high resolution voxel grid by utilizing streaming and parallel computation. The output is a photo-realistic 3D scene model in a volumetric or point-based representation. ... continued below

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Kim, H; Duchaineau, M & Max, N September 21, 2011.

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We present a new scalable volumetric reconstruction algorithm for multi-view stereo using a graphics processing unit (GPU). It is an effectively parallelized GPU algorithm that simultaneously uses a large number of GPU threads, each of which performs voxel carving, in order to integrate depth maps with images from multiple views. Each depth map, triangulated from pair-wise semi-dense correspondences, represents a view-dependent surface of the scene. This algorithm also provides scalability for large-scale scene reconstruction in a high resolution voxel grid by utilizing streaming and parallel computation. The output is a photo-realistic 3D scene model in a volumetric or point-based representation. We demonstrate the effectiveness and the speed of our algorithm with a synthetic scene and real urban/outdoor scenes. Our method can also be integrated with existing multi-view stereo algorithms such as PMVS2 to fill holes or gaps in textureless regions.

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PDF-file: 8 pages; size: 9.4 Mbytes

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  • Presented at: IVCNZ 2011 : Twenty-sixth International Conference Image and Vision Computing New Zealand, Auckland, New Zealand, Nov 29 - Dec 01, 2011

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  • Report No.: LLNL-CONF-500954
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 1035961
  • Archival Resource Key: ark:/67531/metadc831231

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  • September 21, 2011

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  • May 19, 2016, 3:16 p.m.

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  • Nov. 28, 2016, 6:55 p.m.

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Kim, H; Duchaineau, M & Max, N. GPU-based Scalable Volumetric Reconstruction for Multi-view Stereo, article, September 21, 2011; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc831231/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.