VolumeDeform: Real-Time Volumetric Non-rigid Reconstruction

Innmann M, Zollhöfer M, Nießner M, Theobald C, Stamminger M (2016)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2016


Publisher: Springer Verlag

City/Town: Cham

Pages Range: 362-379

Conference Proceedings Title: ECCV 2016 - Proceedings of the European Conference on Computer Vision

Event location: Amsterdam NL

ISBN: 9783319464831

URI: https://www.lgdv.tf.fau.de/?p=425

DOI: 10.1007/978-3-319-46484-8_22


We present a novel approach for the reconstruction of dynamic geometric shapes using a single hand-held consumer-grade RGB-D sensor at real-time rates. Our method builds up the scene model from scratch during the scanning process, thus it does not require a predefined shape template to start with. Geometry and motion are parameterized in a unified manner by a volumetric representation that encodes a distance field of the surface geometry as well as the non-rigid space deformation. Motion tracking is based on a set of extracted sparse color features in combination with a dense depth constraint. This enables accurate tracking and drastically reduces drift inherent to standard modelto- depth alignment. We cast finding the optimal deformation of space as a non-linear regularized variational optimization problem by enforcing local smoothness and proximity to the input constraints. The problem is tackled in real-time at the camera’s capture rate using a data-parallel flip-flop optimization strategy. Our results demonstrate robust tracking even for fast motion and scenes that lack geometric features.

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Innmann, M., Zollhöfer, M., Nießner, M., Theobald, C., & Stamminger, M. (2016). VolumeDeform: Real-Time Volumetric Non-rigid Reconstruction. In Springer International Publishing (Eds.), ECCV 2016 - Proceedings of the European Conference on Computer Vision (pp. 362-379). Amsterdam, NL: Cham: Springer Verlag.


Innmann, Matthias, et al. "VolumeDeform: Real-Time Volumetric Non-rigid Reconstruction." Proceedings of the 14th European Conference on Computer Vision (ECCV), Amsterdam Ed. Springer International Publishing, Cham: Springer Verlag, 2016. 362-379.

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