Cited by 3,959Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging3D Surveying and Cultural Heritage

MonoSLAM: Real-time single camera SLAM

Davison, Andrew J., Reid, Ian D., Molton, Nicholas D., Stasse, Olivier·2007·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to Structure from Motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera.

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Crossref · 10.1109/tpami.2007.1049

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  • UVIO uses a transformer backbone to jointly learn from visual and IMU inputs, improving pose estimation in dynamic environments.

    “For example, UVIO [146] employs a transformer backbone to jointly learn from visual and IMU inputs, significantly improving pose estimation in dynamic environments.”

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Authors
Davison, A. J., Reid, I. D., Molton, N. D., & Stasse, O.
Affiliations
  • University of Oxford (GB)
  • Centre National de la Recherche Scientifique (FR)
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
2007-06
Volume
29
Issue
6
Pages
1052-1067
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
OpenAlex
W2152671441
Cited by
3,959
References
57
Citations by year
2026: 108 · 2025: 240 · 2024: 242 · 2023: 253 · 2022: 246 · 2021: 253 · 2020: 264 · 2019: 271 · 2018: 240 · 2017: 201 · 2016: 179 · 2015: 237 · 2014: 204 · 2013: 205 · 2012: 176
FWCI
328.21
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
  • PubMed (publishedVersion)
  • Spiral (Imperial College London) (submittedVersion)
Funders
Engineering and Physical Sciences Research Council (GR/R76790/02, GR/T24685/01, GR/R76790/01)
Topics
  • Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
  • Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
Keywords
monocular SLAM, real-time SLAM, monocular camera, 3D trajectory estimation, natural landmarks, probabilistic mapping, feature initialization, 3D localization, humanoid robots, augmented reality, handheld camera
MeSH terms
Algorithms, Artificial Intelligence, Computer Systems, Image Enhancement, Image Interpretation, Computer-Assisted, Numerical Analysis, Computer-Assisted, Pattern Recognition, Automated, Photogrammetry, Signal Processing, Computer-Assisted, Video Recording, Information Storage and Retrieval, Imaging, Three-Dimensional

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