The DOI matches its Crossref record; 158 of the 158 references it cites were found in a registry or an index.
Visual SLAM and Structure from Motion in Dynamic Environments: A Survey
Abstract
In the last few decades, Structure from Motion (SfM) and visual Simultaneous Localization and Mapping (visual SLAM) techniques have gained significant interest from both the computer vision and robotic communities. Many variants of these techniques have started to make an impact in a wide range of applications, including robot navigation and augmented reality. However, despite some remarkable results in these areas, most SfM and visual SLAM techniques operate based on the assumption that the observed environment is static. However, when faced with moving objects, overall system accuracy can be jeopardized. In this article, we present for the first time a survey of visual SLAM and SfM techniques that are targeted toward operation in dynamic environments. We identify three main problems: how to perform reconstruction (robust visual SLAM), how to segment and track dynamic objects, and how to achieve joint motion segmentation and reconstruction. Based on this categorization, we provide a comprehensive taxonomy of existing approaches. Finally, the advantages and disadvantages of each solution class are critically discussed from the perspective of practicality and robustness.
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Cites
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Cited by
Xiao, L., Wang, J., Qiu, X., Rong, Z., & Zou, X. (2019) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2019.03.012 · Cited by 348
Deep Learning for Visual Localization and Mapping: A Survey
Chen, C., Wang, B., Lu, C. X., Trigoni, N., & Markham, A. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3309809 · Cited by 97
Self-citationA Survey on Visual Navigation and Positioning for Autonomous UUVs
Qin, J., Li, M., Li, D., Zhong, J., & Yang, K. (2022) · Remote Sensing · doi:10.3390/rs14153794 · Cited by 65
Metadata
- Authors
- Saputra, M. R. U., Markham, A., & Trigoni, N.
- Venue
- ACM Computing Surveys
- Published
- 2018-02-20
- Volume
- 51
- Issue
- 2
- Pages
- 1-36
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2788608285
- Cited by
- 398
- References
- 158
- FWCI
- 35.00
- Type
- journal article
- Language
- en
- Open access
- closed
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