Cited by 17Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging3D Surveying and Cultural Heritage

Survey and Research Challenges in Monocular Visual Odometry

Neyestani, Arman, Picariello, Francesco, Basiri, Amin, Daponte, Pasquale, Vito, Luca De·2023·2023 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv)

Abstract

This study discusses traditional techniques and deep learning-based methodologies for monocular visual odometry. The paper presents an overview of state-of-the-art methods that could be useful for displacement measurement applications. From the review of the state of art, it has been seen in particular that new deep learning-based methods may reduce dependencies on the equipment in the system, with respect to traditional methods.

Integrity signals

Registry

Crossref · 10.1109/metrolivenv56897.2023.10164057

Cites

38 of 38 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Cites

Flagged first, then by citations

1 of the 39 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Neyestani, A., Picariello, F., Basiri, A., Daponte, P., & Vito, L. D.
Affiliations
University of Sannio (IT)
Venue
2023 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv)
Publisher
IEEE
Published
2023-05-29
Pages
107-112
OpenAlex
W4383097518
Cited by
17
References
39
Citations by year
2026: 2 · 2025: 7 · 2024: 6 · 2023: 2
FWCI
9.00
Type
conference paper
Language
en
Open access
closed
Locations
IEEE International Workshop on Metrology for Living Environment (MetroLivEnv) (publishedVersion)
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 visual odometry, displacement measurement

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review