The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
3-D Mapping With an RGB-D Camera
Abstract
In this paper, we present a novel mapping system that robustly generates highly accurate 3-D maps using an RGB-D camera. Our approach requires no further sensors or odometry. With the availability of low-cost and light-weight RGB-D sensors such as the Microsoft Kinect, our approach applies to small domestic robots such as vacuum cleaners, as well as flying robots such as quadrocopters. Furthermore, our system can also be used for free-hand reconstruction of detailed 3-D models. In addition to the system itself, we present a thorough experimental evaluation on a publicly available benchmark dataset. We analyze and discuss the influence of several parameters such as the choice of the feature descriptor, the number of visual features, and validation methods. The results of the experiments demonstrate that our system can robustly deal with challenging scenarios such as fast camera motions and feature-poor environments while being fast enough for online operation. Our system is fully available as open source and has already been widely adopted by the robotics community.
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Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
Speeded-Up Robust Features (SURF)
Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.09.014 · Cited by 13,557 · cited 6×
“We evaluated SIFT, SURF, ORB, and a combination of the Shi- Tomasi detector with SURF descriptors.”
InfluentialShi, J., & Tomasi (1994) · Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94 · doi:10.1109/cvpr.1994.323794 · Cited by 7,724
Parallel Tracking and Mapping for Small AR Workspaces
Klein, G., & Murray, D. (2007) · 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2007.4538852 · Cited by 4,346
Simultaneous localization and mapping: part I
Durrant-Whyte, H., & Bailey, T. (2006) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2006.1638022 · Cited by 4,199
Inference on networks of mixtures for robust robot mapping
Olson, E., & Agarwal, P. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913479413 · Cited by 252
Cited by
ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras
Mur-Artal, R., & Tardos, J. D. (2017) · IEEE Transactions on Robotics · doi:10.1109/tro.2017.2705103 · Cited by 6,898
“In Table III we compare our accuracy to the following state-of-the-art methods: ElasticFusion [15], Kintinuous [12], DVO-SLAM [14] and RGB-D SLAM [13].”
MethodInfluentialORB-SLAM: A Versatile and Accurate Monocular SLAM System
Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2463671 · Cited by 6,778
Deep learning for detecting robotic grasps
Lenz, I., Lee, H., & Saxena, A. (2015) · The International Journal of Robotics Research · doi:10.1177/0278364914549607 · Cited by 1,634
Labbé, M., & Michaud, F. (2019) · Journal of Field Robotics · doi:10.1002/rob.21831 · Cited by 989
PL-SLAM: Real-time monocular visual SLAM with points and lines
Pumarola, A., Vakhitov, A., Agudo, A., Sanfeliu, A., & Moreno-Noguer, F. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2017.7989522 · Cited by 482
Metadata
- Authors
- Endres, F., Hess, J., Sturm, J., Cremers, D., & Burgard, W.
- Venue
- IEEE Transactions on Robotics
- Published
- 2014-02
- Volume
- 30
- Issue
- 1
- Pages
- 177-187
- ISSN
- 1552-3098 (ISSN-L)
- 1941-0468
- OpenAlex
- W2069479606
- Cited by
- 820
- References
- 7
- FWCI
- 69.67
- Type
- journal article
- Language
- en
- Open access
- closed
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- Endres, F., Hess, J., Sturm, J., Cremers, D., & Burgard, W. (2014). 3-D Mapping With an RGB-D Camera. IEEE Transactions on Robotics. https://doi.org/10.1109/tro.2013.2279412
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