以室内场景理解为重点的6D物体姿态估计研究综述

Negar Nejatishahidin, Pooya Fayyazsanavi
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引用次数: 0

摘要

6D目标姿态估计问题在计算机视觉和机器人领域得到了广泛的研究。它具有广泛的应用,如机器人操作,增强现实和3D场景理解。随着深度学习的出现,已经取得了许多突破;然而,当它们遇到看不见的实例、新类别或现实世界的挑战(如杂乱的背景和遮挡)时,方法继续挣扎。在本研究中,我们将探索基于输入模式、问题表述以及是类别级还是实例级方法的可用方法。作为我们讨论的一部分,我们将重点关注如何使用6D对象姿态估计来理解3D场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding
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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