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Mobile Surface Reflectometry
File(s)
EG-cgf-final-June2015-lowres.pdf (710.22 KB)
Accepted version
Author(s)
Riviere, J
Peers, P
Ghosh, A
Type
Journal Article
Abstract
We present two novel mobile reflectometry approaches for acquiring detailed spatially varying isotropic surface
reflectance and mesostructure of a planar material sample using commodity mobile devices. The first approach
relies on the integrated camera and flash pair present on typical mobile devices to support free-form handheld
acquisition of spatially varying rough specular material samples. The second approach, suited for highly specular
samples, uses the LCD panel to illuminate the sample with polarized second order gradient illumination. To
address the limited overlap of the front facing camera’s view and the LCD illumination (and thus limited sample
size), we propose a novel appearance transfer method that combines controlled reflectance measurement of a small
exemplar section with uncontrolled reflectance measurements of the full sample under natural lighting. Finally,
we introduce a novel surface detail enhancement method that adds fine scale surface mesostructure from close-up
observations under uncontrolled natural lighting. We demonstrate the accuracy and versatility of the proposed
mobile reflectometry methods on a wide variety of spatially varying materials.
Date Issued
2016-02-25
Date Acceptance
2015-06-20
Citation
Computer Graphics Forum, 2016, 35 (1), pp.191-202
URI
http://hdl.handle.net/10044/1/24031
DOI
https://www.dx.doi.org/10.1111/cgf.12719
ISSN
1467-8659
Publisher
Wiley
Start Page
191
End Page
202
Journal / Book Title
Computer Graphics Forum
Volume
35
Issue
1
Copyright Statement
This is the peer reviewed version of the following article: Riviere, J., Peers, P. and Ghosh, A. (2016), Mobile Surface Reflectometry. Computer Graphics Forum, 35: 191–202, which has been published in final form at https://dx.doi.org/10.1111/cgf.12719. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
License URL
http://www.rioxx.net/licenses/all-rights-reserved
Sponsor
The Royal Society
Engineering & Physical Science Research Council (EPSRC)
Google
Grant Number
WM 120040
EP/M00192X/1
2013_R2_329
Subjects
Software Engineering
0801 Artificial Intelligence And Image Processing
Publication Status
Published
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