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

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Date
2019
Journal Title
Journal ISSN
Volume Title
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.
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@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
} }
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