ISSN :2582-9793

Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding

Review Article (Published On: 31-Dec-2022 )
Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding
DOI : https://dx.doi.org/10.54364/AAIML.2022.1141

Negar Nejatishahidin and Pooya Fayyazsanavi

Adv. Artif. Intell. Mach. Learn., 2 (4):588-613

Negar Nejatishahidin : George Mason University

Pooya Fayyazsanavi : Research assistant

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DOI: https://dx.doi.org/10.54364/AAIML.2022.1141

Article History: Received on: 05-Dec-22, Accepted on: 18-Dec-22, Published on: 31-Dec-22

Corresponding Author: Negar Nejatishahidin

Email: nnejatis@gmu.edu

Citation: Negar Nejatishahidin (2022). Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding. Adv. Artif. Intell. Mach. Learn., 2 (4 ):588-613


Abstract

    

6D object pose estimation problem has been extensively studied in the field of Computer Vision and Robotics. It has wide range of applications such as robot manipulation, augmented reality, and 3D scene understanding. With the advent of Deep Learning, many breakthroughs have been made; however, approaches continue to struggle when they encounter unseen instances, new categories, or real-world challenges such as cluttered backgrounds and occlusions. In this study, we will explore the available methods based on input modality, problem formulation, and whether it is a category-level or instance-level approach. As a part of our discussion, we will focus on how 6D object pose estimation can be used for understanding 3D scenes.

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