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Weighted Patch-Based Reconstruction: Linking (Multi-view) Stereo to Scale Space

Klowsky, Ronny and Kuijper, Arjan and Goesele, Michael (2013):
Weighted Patch-Based Reconstruction: Linking (Multi-view) Stereo to Scale Space.
In: Lecture Notes in Computer Science (LNCS); 7893, pp. 234-245, Springer, Berlin, Heidelberg, New York, Scale Space and Variational Methods in Computer Vision, DOI: 10.1007/978-3-642-38267-3₂₀,
[Conference or Workshop Item]

Abstract

Surface reconstruction using patch-based multi-view stereo commonly assumes that the underlying surface is locally planar. This is typically not true so that least-squares fitting of a planar patch leads to systematic errors which are of particular importance for multi-scale surface reconstruction. In a recent paper, we determined the modulation transfer function of a classical patch-based stereo system. Our key insight was that the reconstructed surface is a box-filtered version of the original surface. Since the box filter is not a true low-pass filter this causes high-frequency artifacts In this paper, we propose an extended reconstruction model by weighting the least-squares fit of the 3D patch. We show that if the weighting function meets specified criteria the reconstructed surface is the convolution of the original surface with that weighting function. A choice of particular interest is the Gaussian which is commonly used in image and signal processing but left unexploited by many multi-view stereo algorithms. Finally, we demonstrate the effects of our theoretic findings using experiments on synthetic and real-world data sets.

Item Type: Conference or Workshop Item
Erschienen: 2013
Creators: Klowsky, Ronny and Kuijper, Arjan and Goesele, Michael
Title: Weighted Patch-Based Reconstruction: Linking (Multi-view) Stereo to Scale Space
Language: English
Abstract:

Surface reconstruction using patch-based multi-view stereo commonly assumes that the underlying surface is locally planar. This is typically not true so that least-squares fitting of a planar patch leads to systematic errors which are of particular importance for multi-scale surface reconstruction. In a recent paper, we determined the modulation transfer function of a classical patch-based stereo system. Our key insight was that the reconstructed surface is a box-filtered version of the original surface. Since the box filter is not a true low-pass filter this causes high-frequency artifacts In this paper, we propose an extended reconstruction model by weighting the least-squares fit of the 3D patch. We show that if the weighting function meets specified criteria the reconstructed surface is the convolution of the original surface with that weighting function. A choice of particular interest is the Gaussian which is commonly used in image and signal processing but left unexploited by many multi-view stereo algorithms. Finally, we demonstrate the effects of our theoretic findings using experiments on synthetic and real-world data sets.

Series Name: Lecture Notes in Computer Science (LNCS); 7893
Publisher: Springer, Berlin, Heidelberg, New York
Uncontrolled Keywords: Business Field: Digital society, Research Area: Generalized digital documents, Multi-view stereo, Surface reconstruction, Patch-based depth reconstruction
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Scale Space and Variational Methods in Computer Vision
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1007/978-3-642-38267-3₂₀
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