Shadow and Specularity Priors for Intrinsic Light Field Decomposition

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2018
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LIA - Light Field Imaging and Analysis
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PELILLO, Marcello, ed., Edwin HANCOCK, ed.. International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition EMMCVPR 2017: Energy Minimization Methods in Computer Vision and Pattern Recognition. Cham: Springer, 2018, pp. 389-406. Lecture Notes in Computer Science. 10746. ISBN 978-3-319-78198-3. Available under: doi: 10.1007/978-3-319-78199-0_26
Zusammenfassung

In this work, we focus on the problem of intrinsic scene decomposition in light fields. Our main contribution is a novel prior to cope with cast shadows and inter-reflections. In contrast to other approaches which model inter-reflection based only on geometry, we model indirect shading by combining geometric and color information. We compute a shadow confidence measure for the light field and use it in the regularization constraints. Another contribution is an improved specularity estimation by using color information from sub-aperture views. The new priors are embedded in a recent framework to decompose the input light field into albedo, shading, and specularity. We arrive at a variational model where we regularize albedo and the two shading components on epipolar plane images, encouraging them to be consistent across all sub-aperture views. Our method is evaluated on ground truth synthetic datasets and real world light fields. We outperform both state-of-the art approaches for RGB+D images and recent methods proposed for light fields.

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11th International Conference, EMMCVPR 2017, 30. Okt. 2017 - 1. Nov. 2017, Venice, Italy
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ISO 690ALPEROVICH, Anna, Ole JOHANNSEN, Michael STRECKE, Bastian GOLDLÜCKE, 2018. Shadow and Specularity Priors for Intrinsic Light Field Decomposition. 11th International Conference, EMMCVPR 2017. Venice, Italy, 30. Okt. 2017 - 1. Nov. 2017. In: PELILLO, Marcello, ed., Edwin HANCOCK, ed.. International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition EMMCVPR 2017: Energy Minimization Methods in Computer Vision and Pattern Recognition. Cham: Springer, 2018, pp. 389-406. Lecture Notes in Computer Science. 10746. ISBN 978-3-319-78198-3. Available under: doi: 10.1007/978-3-319-78199-0_26
BibTex
@inproceedings{Alperovich2018Shado-42891,
  year={2018},
  doi={10.1007/978-3-319-78199-0_26},
  title={Shadow and Specularity Priors for Intrinsic Light Field Decomposition},
  number={10746},
  isbn={978-3-319-78198-3},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition  EMMCVPR 2017: Energy Minimization Methods in Computer Vision and Pattern Recognition},
  pages={389--406},
  editor={Pelillo, Marcello and Hancock, Edwin},
  author={Alperovich, Anna and Johannsen, Ole and Strecke, Michael and Goldlücke, Bastian}
}
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