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Conference Papers Year : 2012

Bundle Adjustment Constrained Smoothing for Multi-view Point Cloud Data

Kun Liu
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  • PersonId : 933925

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Rhaleb Zayer
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  • PersonId : 933923

Abstract

Direct use of denoising and mesh reconstruction algorithms on point clouds originating from multi-view images is often oblivious to the reprojection error. This can be a severe limitation in applications which require accurate point tracking, e.g., metrology. In this paper, we propose a method for improving the quality of such data without forfeiting the original matches. We formulate the problem as a robust smoothness cost function constrained by a bounded reprojection error. The arising optimization problem is addressed as a sequence of unconstrained optimization problems by virtue of the barrier method. Substantiated experiments on synthetic and acquired data compare our approach to alternative techniques.
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Dates and versions

hal-00763442 , version 1 (10-12-2012)

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Kun Liu, Rhaleb Zayer. Bundle Adjustment Constrained Smoothing for Multi-view Point Cloud Data. SVC 2012, 8th International Symposium on Visual Computing, Jul 2012, Rethymnon, Crete, Greece. pp.126-137, ⟨10.1007/978-3-642-33179-4_13⟩. ⟨hal-00763442⟩
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