Submap-based bundle adjustment for 3D reconstruction from RGB-D data
Maier R, Sturm J, Cremers D (2014)
Publication Type: Conference contribution
Publication year: 2014
Journal
Publisher: Springer Verlag
Book Volume: 8753
Pages Range: 54-65
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Münster, DEU
ISBN: 9783319117515
DOI: 10.1007/978-3-319-11752-2_5
Abstract
The key contribution of this paper is a novel submapping technique for RGB-D-based bundle adjustment. Our approach significantly speeds up 3D object reconstruction with respect to full bundle adjustment while generating visually compelling 3D models of high metric accuracy. While submapping has been explored previously for mono and stereo cameras, we are the first to transfer and adapt this concept to RGB-D sensors and to provide a detailed analysis of the resulting gain. In our approach, we partition the input data uniformly into submaps to optimize them individually by minimizing the 3D alignment error. Subsequently, we fix the interior variables and optimize only over the separator variables between the submaps. As we demonstrate in this paper, our method reduces the runtime of full bundle adjustment by 32% on average while still being able to deal with real-world noise of cheap commodity sensors. We evaluated our method on a large number of benchmark datasets, and found that we outperform several stateof- the-art approaches both in terms of speed and accuracy. Furthermore, we present highly accurate 3D reconstructions of various objects to demonstrate the validity of our approach
Involved external institutions
Germany (DE)How to cite
APA:
Maier, R., Sturm, J., & Cremers, D. (2014). Submap-based bundle adjustment for 3D reconstruction from RGB-D data. In Joachim Hornegger, Xiaoyi Jiang, Joachim Hornegger, Joachim Hornegger, Reinhard Koch (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 54-65). Münster, DEU: Springer Verlag.
MLA:
Maier, Robert, Juergen Sturm, and Daniel Cremers. "Submap-based bundle adjustment for 3D reconstruction from RGB-D data." Proceedings of the 36th German Conference on Pattern Recognition, GCPR 2014, Münster, DEU Ed. Joachim Hornegger, Xiaoyi Jiang, Joachim Hornegger, Joachim Hornegger, Reinhard Koch, Springer Verlag, 2014. 54-65.
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