Large-scale multi-resolution surface reconstruction from RGB-D sequences
Steinbruecker F, Kerl C, Sturm J, Cremers D (2013)
Publication Type: Conference contribution
Publication year: 2013
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 3264-3271
Conference Proceedings Title: Proceedings of the IEEE International Conference on Computer Vision
Event location: AUS
ISBN: 9781479928392
Abstract
We propose a method to generate highly detailed, textured 3D models of large environments from RGB-D sequences. Our system runs in real-time on a standard desktop PC with a state-of-the-art graphics card. To reduce the memory consumption, we fuse the acquired depth maps and colors in a multi-scale octree representation of a signed distance function. To estimate the camera poses, we construct a pose graph and use dense image alignment to determine the relative pose between pairs of frames. We add edges between nodes when we detect loop-closures and optimize the pose graph to correct for long-term drift. Our implementation is highly parallelized on graphics hardware to achieve real-time performance. More specifically, we can reconstruct, store, and continuously update a colored 3D model of an entire corridor of nine rooms at high levels of detail in real-time on a single GPU with 2.5GB. © 2013 IEEE.
Involved external institutions
Germany (DE)How to cite
APA:
Steinbruecker, F., Kerl, C., Sturm, J., & Cremers, D. (2013). Large-scale multi-resolution surface reconstruction from RGB-D sequences. In Proceedings of the IEEE International Conference on Computer Vision (pp. 3264-3271). AUS: Institute of Electrical and Electronics Engineers Inc..
MLA:
Steinbruecker, Frank, et al. "Large-scale multi-resolution surface reconstruction from RGB-D sequences." Proceedings of the 2013 14th IEEE International Conference on Computer Vision, ICCV 2013, AUS Institute of Electrical and Electronics Engineers Inc., 2013. 3264-3271.
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