Intrinsic3D: High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting
Maier R, Kim K, Cremers D, Kautz J, Niessner M (2017)
Publication Type: Conference contribution
Publication year: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2017-October
Pages Range: 3133-3141
Conference Proceedings Title: Proceedings of the IEEE International Conference on Computer Vision
Event location: Venice, ITA
ISBN: 9781538610329
Abstract
We introduce a novel method to obtain high-quality 3D reconstructions from consumer RGB-D sensors. Our core idea is to simultaneously optimize for geometry encoded in a signed distance field (SDF), textures from automatically-selected keyframes, and their camera poses along with material and scene lighting. To this end, we propose a joint surface reconstruction approach that is based on Shape-from-Shading (SfS) techniques and utilizes the estimation of spatially-varying spherical harmonics (SVSH) from subvolumes of the reconstructed scene. Through extensive examples and evaluations, we demonstrate that our method dramatically increases the level of detail in the reconstructed scene geometry and contributes highly to consistent surface texture recovery.
Involved external institutions
United States (USA) (US)
Germany (DE)How to cite
APA:
Maier, R., Kim, K., Cremers, D., Kautz, J., & Niessner, M. (2017). Intrinsic3D: High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting. In Proceedings of the IEEE International Conference on Computer Vision (pp. 3133-3141). Venice, ITA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Maier, Robert, et al. "Intrinsic3D: High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting." Proceedings of the 16th IEEE International Conference on Computer Vision, ICCV 2017, Venice, ITA Institute of Electrical and Electronics Engineers Inc., 2017. 3133-3141.
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