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Cell-based approach for 3D reconstruction from incomplete silhouettes

Maarten Slembrouck UGent, Peter Veelaert UGent, David Van Hamme UGent, Dimitri Van Cauwelaert UGent and Wilfried Philips UGent (2017) Lecture Notes in Computer Science.
abstract
Shape-from-silhouettes is a widely adopted approach to compute accurate 3D reconstructions of people or objects in a multi-camera environment. However, such algorithms are traditionally very sensitive to errors in the silhouettes due to imperfect foreground-background estimation or occluding objects appearing in front of the object of interest. We propose a novel algorithm that is able to still provide high quality reconstruction from incomplete silhouettes. At the core of the method is the partitioning of reconstruction space in cells, i.e. regions with uniform camera and silhouette coverage properties. A set of rules is proposed to iteratively add cells to the reconstruction based on their potential to explain discrepancies between silhouettes in different cameras. Experimental analysis shows significantly improved F1-scores over standard leave-M-out reconstruction techniques.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (other)
publication status
published
subject
keyword
shape-from-silhouettes, 3D reconstruction, occlusion, multi-camera
in
Lecture Notes in Computer Science
publisher
Springer
conference name
Advanced Concepts for Intelligent Vision Systems (ACIVS)
conference organizer
University of Antwerp
conference location
Antwerp
conference start
2017-09-18
conference end
2017-09-21
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
8534000
handle
http://hdl.handle.net/1854/LU-8534000
date created
2017-10-12 12:27:10
date last changed
2017-11-20 13:03:48
@inproceedings{8534000,
  abstract     = {Shape-from-silhouettes is a widely adopted approach to compute accurate 3D reconstructions of people or objects in a multi-camera environment. However, such algorithms are traditionally very sensitive to errors in the silhouettes due to imperfect foreground-background estimation or occluding objects appearing in front of the object of interest. We propose a novel algorithm that is able to still provide high quality reconstruction from incomplete silhouettes. At the core of the method is the partitioning of reconstruction space in cells, i.e. regions with uniform camera and silhouette coverage properties. A set of rules is proposed to iteratively add cells to the reconstruction based on their potential to explain discrepancies between silhouettes in different cameras. Experimental analysis shows significantly improved F1-scores over standard leave-M-out reconstruction techniques.},
  author       = {Slembrouck, Maarten and Veelaert, Peter and Van Hamme, David and Van Cauwelaert, Dimitri and Philips, Wilfried},
  booktitle    = {Lecture Notes in Computer Science},
  keyword      = {shape-from-silhouettes,3D reconstruction,occlusion,multi-camera},
  language     = {eng},
  location     = {Antwerp},
  publisher    = {Springer},
  title        = {Cell-based approach for 3D reconstruction from incomplete silhouettes},
  year         = {2017},
}

Chicago
Slembrouck, Maarten, Peter Veelaert, David Van Hamme, Dimitri Van Cauwelaert, and Wilfried Philips. 2017. “Cell-based Approach for 3D Reconstruction from Incomplete Silhouettes.” In Lecture Notes in Computer Science. Springer.
APA
Slembrouck, M., Veelaert, P., Van Hamme, D., Van Cauwelaert, D., & Philips, W. (2017). Cell-based approach for 3D reconstruction from incomplete silhouettes. Lecture Notes in Computer Science. Presented at the Advanced Concepts for Intelligent Vision Systems (ACIVS), Springer.
Vancouver
1.
Slembrouck M, Veelaert P, Van Hamme D, Van Cauwelaert D, Philips W. Cell-based approach for 3D reconstruction from incomplete silhouettes. Lecture Notes in Computer Science. Springer; 2017.
MLA
Slembrouck, Maarten, Peter Veelaert, David Van Hamme, et al. “Cell-based Approach for 3D Reconstruction from Incomplete Silhouettes.” Lecture Notes in Computer Science. Springer, 2017. Print.