Normal Map Bias Reduction for Many-Lights Multi-View Photometric Stereo

Gan, Jiangbin; Bergen, Philipp; Thormählen, Thorsten; Drescher, Philip; Hagens, Ralf

Normal Map Bias Reduction for Many-Lights Multi-View Photometric Stereo

Files

019-025.pdf (5.7 MB)

Date

2019

Authors

Gan, Jiangbin
Bergen, Philipp
Thormählen, Thorsten
Drescher, Philip
Hagens, Ralf

Publisher

The Eurographics Association

Abstract

In this paper, we improve upon an existing many-lights multi-view photometric stereo approach. Firstly, we show how to detect continuous regions for normal integration, which leads to a fully automatic reconstruction pipeline. Secondly, we compute perpixel light source visibilities using an initial biased reconstruction in order to update the estimated normal map to a solution with reduced bias. Thirdly, to further improve the normal accuracy, we compensate for interreflections of light between surface locations. Our approach is evaluated on both synthetic and real-world data and it is shown that the normal accuracy is improved by around 50 percent.

        @inproceedings{10.2312:vmv.20191314
,
booktitle = {Vision, Modeling and Visualization
},
editor = {Schulz, Hans-Jörg and Teschner, Matthias and Wimmer, Michael
},
title = {{Normal Map Bias Reduction for Many-Lights Multi-View Photometric Stereo
}},
author = {Gan, Jiangbin and 
Bergen, Philipp and 
Thormählen, Thorsten and 
Drescher, Philip and 
Hagens, Ralf
},
year = {2019
},
publisher = {The Eurographics Association
},
ISBN = {978-3-03868-098-7
},
DOI = {10.2312/vmv.20191314
}
}