Simultaneous Surface Segmentation and BRDF Estimation via Bayesian Methods

Malte Lenoch, Thorsten Wilhelm, Christian Wöhler

2016

Abstract

We present a novel procedure that achieves segmentation of an arbitrary surface relying on the maximum a-posteriori estimation of its reflectance parameters. The number of surfaces segments is computed by the algorithm without user intervention. We employ Markov Chain Monte Carlo algorithms to compute the probability distributions associated with the model parameters of a Blinn reflectance model based on the input images. The fact that parameters are treated as probability distributions enables us to directly draw additional information about the certainty of the estimation from the results of both parameters and segmentation borders. Reversible jump MCMC allows us to include an unspecified number of change points in the computation, such that the algorithm explores model and parameter space at the same time and derives a segmentation of the surface from the input data. To accomplish this, we extend the existing concept of change points to two dimensions introducing a number of necessary new regulations and properties. The performance of the segmentation and reflectance estimation is evaluated on a synthetic and a real-world dataset.

Paper Citation

in Harvard Style

Lenoch M., Wilhelm T. and Wöhler C. (2016). Simultaneous Surface Segmentation and BRDF Estimation via Bayesian Methods . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 39-48. DOI: 10.5220/0005722600390048

in Bibtex Style

@conference{visapp16,
author={Malte Lenoch and Thorsten Wilhelm and Christian Wöhler},
title={Simultaneous Surface Segmentation and BRDF Estimation via Bayesian Methods},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={39-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005722600390048},
isbn={978-989-758-175-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)
TI - Simultaneous Surface Segmentation and BRDF Estimation via Bayesian Methods
SN - 978-989-758-175-5
AU - Lenoch M.
AU - Wilhelm T.
AU - Wöhler C.
PY - 2016
SP - 39
EP - 48
DO - 10.5220/0005722600390048