Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction

Two-dimensional object detection techniques can detect multiscale objects in images. However, they lack depth information. Three-dimensional object detection provides the location of the object in the image along with depth information. To provide depth information, 3D object detection involves the...

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Main Authors: Tajbia Karim, Zainal Rasyid Mahayuddin, Mohammad Kamrul Hasan
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/13/24/13267
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author Tajbia Karim
Zainal Rasyid Mahayuddin
Mohammad Kamrul Hasan
author_facet Tajbia Karim
Zainal Rasyid Mahayuddin
Mohammad Kamrul Hasan
author_sort Tajbia Karim
collection DOAJ
description Two-dimensional object detection techniques can detect multiscale objects in images. However, they lack depth information. Three-dimensional object detection provides the location of the object in the image along with depth information. To provide depth information, 3D object detection involves the application of depth-perceiving sensors such as LiDAR, stereo cameras, RGB-D, RADAR, etc. The existing review articles on 3D object detection techniques are found to be focusing on either a singular modality (e.g., only LiDAR point cloud-based) or a singular application field (e.g., autonomous vehicle navigation). However, to the best of our knowledge, there is no review paper that discusses the applicability of 3D object detection techniques in other fields such as agriculture, robot vision or human activity detection. This study analyzes both singular and multimodal techniques of 3D object detection techniques applied in different fields. A critical analysis comprising strengths and weaknesses of the 3D object detection techniques is presented. The aim of this study is to facilitate future researchers and practitioners to provide a holistic view of 3D object detection techniques. The critical analysis of the singular and multimodal techniques is expected to help the practitioners find the appropriate techniques based on their requirement.
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spelling doaj.art-7866d297c41846beaa2f1360df66dec02023-12-22T13:52:04ZengMDPI AGApplied Sciences2076-34172023-12-0113241326710.3390/app132413267Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research DirectionTajbia Karim0Zainal Rasyid Mahayuddin1Mohammad Kamrul Hasan2Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, MalaysiaCenter for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, MalaysiaCenter for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, MalaysiaTwo-dimensional object detection techniques can detect multiscale objects in images. However, they lack depth information. Three-dimensional object detection provides the location of the object in the image along with depth information. To provide depth information, 3D object detection involves the application of depth-perceiving sensors such as LiDAR, stereo cameras, RGB-D, RADAR, etc. The existing review articles on 3D object detection techniques are found to be focusing on either a singular modality (e.g., only LiDAR point cloud-based) or a singular application field (e.g., autonomous vehicle navigation). However, to the best of our knowledge, there is no review paper that discusses the applicability of 3D object detection techniques in other fields such as agriculture, robot vision or human activity detection. This study analyzes both singular and multimodal techniques of 3D object detection techniques applied in different fields. A critical analysis comprising strengths and weaknesses of the 3D object detection techniques is presented. The aim of this study is to facilitate future researchers and practitioners to provide a holistic view of 3D object detection techniques. The critical analysis of the singular and multimodal techniques is expected to help the practitioners find the appropriate techniques based on their requirement.https://www.mdpi.com/2076-3417/13/24/132673D object detectionsingular techniquemultimodal technique
spellingShingle Tajbia Karim
Zainal Rasyid Mahayuddin
Mohammad Kamrul Hasan
Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction
Applied Sciences
3D object detection
singular technique
multimodal technique
title Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction
title_full Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction
title_fullStr Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction
title_full_unstemmed Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction
title_short Singular and Multimodal Techniques of 3D Object Detection: Constraints, Advancements and Research Direction
title_sort singular and multimodal techniques of 3d object detection constraints advancements and research direction
topic 3D object detection
singular technique
multimodal technique
url https://www.mdpi.com/2076-3417/13/24/13267
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AT zainalrasyidmahayuddin singularandmultimodaltechniquesof3dobjectdetectionconstraintsadvancementsandresearchdirection
AT mohammadkamrulhasan singularandmultimodaltechniquesof3dobjectdetectionconstraintsadvancementsandresearchdirection