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Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions
Review Article  ·  Published: 12 October 2024
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ICCK Transactions on Sensing, Communication, and Control
Volume 1, Issue 1, 2024: 3-29
Review Article Free to Read

Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions

by
Ghulam E Mustafa Abro Ghulam E Mustafa Abro 1 * ORCID
Zain Anwar Ali Zain Anwar Ali 2 ORCID
Summaiya Rajput Summaiya Rajput 3
1 Interdisciplinary Research Centre for Aviation and Space Exploration (IRCASE), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Kingdom of Saudi Arabia
2 Electronic Engineering Department, Maynooth International Engineering College (MIEC), Maynooth University, Maynooth, Co. Kildare, Ireland
3 Department of Telecommunication Engineering, Mehran University of Engineering and Technology (MUET), Pakistan
* Corresponding Author: Ghulam E Mustafa Abro, [email protected]
Volume 1, Issue 1
Volume 1, Issue 1 2024
Received: 13 July 2024 Revised: 20 September 2024 Accepted: 22 September 2024 Published: 12 October 2024 CrossMark
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DOI: 10.62762/TSCC.2024.989358
ARK: ark:/57805/tscc.2024.989358
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Article Information

Published in ICCK Transactions on Sensing, Communication, and Control
Volume/Issue Volume 1, Issue 1, 2024
Pages 3-29
Cited by 18 (Crossref) 22 (Scopus)

Abstract

This review paper offers a thorough assessment of three-dimensional object recognition methods, an essential element in the perception frameworks of autonomous systems. This analysis emphasises the integration of LiDAR and camera sensors, providing a distinctive contrast with more economical alternatives like camera-only or camera-Radar combinations. This study objectively evaluates performance and practical implementation issues, such as cost and operational efficiency, thereby elucidating the limitations of existing systems and proposing avenues for further research. The insights provided render it a significant asset for enhancing 3D object recognition and autonomy in intelligent systems.

Graphical Abstract

Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions

Keywords

autonomous systems camera fusion methods LiDAR object detection radar and three-dimensional

Data Availability Statement

Not applicable.

Funding

This work was supported by the Interdisciplinary Research Centre for Aviation and Space Exploration (IRCASE), King Fahd University of Petroleum and Minerals (KFUPM, Kingdom of Saudi Arabia).

Conflicts of Interest

The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate

Not applicable.

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Abro, G. E. M., Ali, Z. A., & Rajput, S. (2024). Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions. ICCK Transactions on Sensing, Communication, and Control, 1(1), 3-29. https://doi.org/10.62762/TSCC.2024.989358
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TY  - JOUR
AU  - Abro, Ghulam E Mustafa
AU  - Ali, Zain Anwar
AU  - Rajput, Summaiya
PY  - 2024
DA  - 2024/10/12
TI  - Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions
JO  - ICCK Transactions on Sensing, Communication, and Control
T2  - ICCK Transactions on Sensing, Communication, and Control
JF  - ICCK Transactions on Sensing, Communication, and Control
VL  - 1
IS  - 1
SP  - 3
EP  - 29
DO  - 10.62762/TSCC.2024.989358
UR  - https://www.icck.org/article/abs/TSCC.2024.989358
KW  - autonomous systems
KW  - camera
KW  - fusion methods
KW  - LiDAR
KW  - object detection
KW  - radar and three-dimensional
AB  - This review paper offers a thorough assessment of three-dimensional object recognition methods, an essential element in the perception frameworks of autonomous systems. This analysis emphasises the integration of LiDAR and camera sensors, providing a distinctive contrast with more economical alternatives like camera-only or camera-Radar combinations. This study objectively evaluates performance and practical implementation issues, such as cost and operational efficiency, thereby elucidating the limitations of existing systems and proposing avenues for further research. The insights provided render it a significant asset for enhancing 3D object recognition and autonomy in intelligent systems.
SN  - 3068-9287
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -
BibTeX Format
Compatible with LaTeX, BibTeX, and other reference managers
@article{Abro2024Innovation,
  author = {Ghulam E Mustafa Abro and Zain Anwar Ali and Summaiya Rajput},
  title = {Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions},
  journal = {ICCK Transactions on Sensing, Communication, and Control},
  year = {2024},
  volume = {1},
  number = {1},
  pages = {3-29},
  doi = {10.62762/TSCC.2024.989358},
  url = {https://www.icck.org/article/abs/TSCC.2024.989358},
  abstract = {This review paper offers a thorough assessment of three-dimensional object recognition methods, an essential element in the perception frameworks of autonomous systems. This analysis emphasises the integration of LiDAR and camera sensors, providing a distinctive contrast with more economical alternatives like camera-only or camera-Radar combinations. This study objectively evaluates performance and practical implementation issues, such as cost and operational efficiency, thereby elucidating the limitations of existing systems and proposing avenues for further research. The insights provided render it a significant asset for enhancing 3D object recognition and autonomy in intelligent systems.},
  keywords = {autonomous systems, camera, fusion methods, LiDAR, object detection, radar and three-dimensional},
  issn = {3068-9287},
  publisher = {Institute of Central Computation and Knowledge}
}

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ICCK Transactions on Sensing, Communication, and Control
ICCK Transactions on Sensing, Communication, and Control
ISSN: 3068-9287 (Online) | ISSN: 3068-9279 (Print)
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