Single Image Multi-Spectral Photometric Stereo Using a Split U-Shaped CNN

We present a system to extract surface orientation and albedos from a single shot image using three differently colored illumination sources. Photometric stereo allows one to extract local surface information such as normals or gradients. Traditionally, the local orientations and albedos are compute...

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Bibliographic Details
Main Authors: Antensteiner, Doris, Stolc, Svorad, Soukup, Daniel
Format: Conference Proceeding
Language:English
Subjects:
Conferences
Decoding
Image reconstruction
Light sources
Lighting
Shape
Surface reconstruction
Online Access:Request full text
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Description
Summary:We present a system to extract surface orientation and albedos from a single shot image using three differently colored illumination sources. Photometric stereo allows one to extract local surface information such as normals or gradients. Traditionally, the local orientations and albedos are computed using serveral acquisitions of the same viewing angle and under varying illumination directions. In applications with moving objects, where the acquisition-as well as processing speed are essential, such setups are poorly suited. We propose a single shot decomposition using three differently colored light sources under defined illumination directions. To allow for a fast and regularized inference, we built a split U-shaped convolutional neural network, which takes a single shot input and estimates both the surface orientation and albedo simultaneously.
ISSN:2160-7516
DOI:10.1109/CVPRW.2019.00065