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Cited by 2,924

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Direct Sparse Odometry

Engel, Jakob, Koltun, Vladlen, Cremers, Daniel·2018·IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI 10.1109/tpami.2017.2658577
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Abstract

Direct Sparse Odometry (DSO) is a visual odometry method based on a novel, highly accurate sparse and direct structure and motion formulation. It combines a fully direct probabilistic model (minimizing a photometric error) with consistent, joint optimization of all model parameters, including geometry-represented as inverse depth in a reference frame-and camera motion. This is achieved in real time by omitting the smoothness prior used in other direct methods and instead sampling pixels evenly throughout the images. Since our method does not depend on keypoint detectors or descriptors, it can naturally sample pixels from across all image regions that have intensity gradient, including edges or smooth intensity variations on essentially featureless walls. The proposed model integrates a full photometric calibration, accounting for exposure time, lens vignetting, and non-linear response functions. We thoroughly evaluate our method on three different datasets comprising several hours of video. The experiments show that the presented approach significantly outperforms state-of-the-art direct and indirect methods in a variety of real-world settings, both in terms of tracking accuracy and robustness.

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Show all 9 references

Research works printed but not linked: 17

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  2. huang, 2008, A first-estimates Jacobian EKF for improving SLAM consistency, Proc IEEE/ASME Int Symp Exp Robot, 619
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  7. li, 2013, Real-time motion estimation on a cellphone using inertial sensing and a rolling-shutter camera, Proc IEEE Int Conf Robot Autom, 4712
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  9. 10.1007/s11263-011-0466-7 · DOI
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  15. 10.1109/ISMAR.2014.6948420 · DOI · Paper page
  16. 10.1109/CVPR.2016.440 · DOI
  17. 10.1007/978-3-642-15986-2_2 · DOI · Paper page

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Metadata

Authors
Engel, J., Koltun, V., & Cremers, D.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2018-03-01
Volume
40
Issue
3
Pages
611-625
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
DOI
10.1109/tpami.2017.2658577
OpenAlex
W2474281075
Cited by
2,924
References
9
FWCI
235.95
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/OAPA.html (vor)
Funders
  • ERC Consolidator
  • Google Faculty Research Award

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CoChat. (2026). Citation check: Direct Sparse Odometry. https://app.cochat.ai/papers/10.1109/tpami.2017.2658577
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Engel, J., Koltun, V., & Cremers, D. (2018). Direct Sparse Odometry. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2017.2658577

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