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Erschienen in:
Reflection Symmetry Detection via Appearance of Structure Descriptor Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Multi-view Inverse Rendering Under Arbitrary Illumination and Albedo

verfasst von : Kichang Kim, Akihiko Torii, Masatoshi Okutomi

Erschienen in: Computer Vision – ECCV 2016

Verlag: Springer International Publishing

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Abstract

3D shape reconstruction with multi-view stereo (MVS) relies on a robust evaluation of photo consistencies across images. The robustness is ensured by isolating surface albedo and scene illumination from the shape recovery, i.e. shading and colour variation are regarded as a nuisance in MVS. This yields a gap in the qualities between the recovered shape and the images used. We present a method to address it by jointly estimating detailed shape, illumination and albedo using the initial shape robustly recovered by MVS. This is achieved by solving the multi-view inverse rendering problem using the geometric and photometric smoothness terms and the normalized spherical harmonics illumination model. Our method allows spatially-varying albedo and per image illumination without any prerequisites such as training data or image segmentation. We demonstrate that our method can clearly improve the 3D shape and recover illumination and albedo on real world scenes.

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Vorheriges Kapitel Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs
Nächstes Kapitel DAPs: Deep Action Proposals for Action Understanding
Fußnoten
1
The gamma calibration using a fixed value (2.2 as in [56]) on the internet photos gave no additional improvement in our preliminary experiments. However, the calibration of nonlinearity will be beneficial when it is performed precisely.
 
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Metadaten
Titel
Multi-view Inverse Rendering Under Arbitrary Illumination and Albedo
verfasst von
Kichang Kim
Akihiko Torii
Masatoshi Okutomi
Copyright-Jahr
2016
Buch
Computer Vision – ECCV 2016

Print ISBN: 978-3-319-46486-2

Electronic ISBN: 978-3-319-46487-9

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-46487-9_46