三维重建的次优视图策略的结构化回顾和分类

Bashar Alsadik , Hussein Alwan Mahdi , Nagham Amer Abdulateef
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引用次数: 0

摘要

次优视点(NBV)策略是一类解决自主机器人传感器选择最佳视点以实现有效和完整的3D场景重建的重要方法。多年来,NBV方法已经从基于规则的方法发展到深度学习驱动的方法。因此,NBV策略已经变得多样化和不分类,这使得研究人员和从业者很难导航或标准化的方法。因此,本文将nvb方法分为五种不同的策略:基于规则的、基于不确定性的、基于抽样的、基于学习的和基于预测的方法。它的目的是在系统地审查了100多份出版物后,给出一个结构化的理解,包括概述关键方法,开放获取工具和各自的应用。每个策略都有相关的研究问题,如理解几何启发式在基于规则的方法中的作用,确定有效的探索抽样机制,利用预测模型进行优化,解决未知环境中的不确定性,以及应用基于学习的技术来增强适应性和性能。提出了一些明确分类的建议,从而有助于将更有组织的框架和跨学科的合作结合在一起。这项工作不仅为初学者和专家研究人员提供了全面的资源,而且使读者能够回答战略特定的研究问题,为NBV规划趋势和新兴观点提供可操作的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A structured review and taxonomy of next-best-view strategies for 3D reconstruction
Next-Best-View (NBV) strategies are a class of approaches that solve the important problem of selecting the best possible viewpoints of an autonomous robot sensor for effective and complete 3D scene reconstruction. NBV methodologies have developed significantly over the years from rule-based approaches to those driven from deep learning. Consequently, NBV strategies have become diverse and uncategorized which makes it difficult for researchers and practitioners to navigate or standardize the methods. Therefore, in this paper, a comprehensive review was conducted to separate NBV methods into five distinct strategies: rule-based, uncertainty-based, sampling-based, learning-based, and prediction-based approaches. It is aimed to give a structured understanding after systematically reviewing over 100 publications including outlining key methodologies, open-access tools, and respective applications. Each strategy is investigated with related research questions such as understanding the role of geometric heuristics in rule-based methods, identifying efficient sampling mechanisms for exploration, leveraging predictive models for optimization, addressing uncertainty in unknown environments, and applying learning-based techniques to enhance adaptability and performance. Some suggestions are made for making classifications explicit, thus helping pull together more organized frameworks and collaborations across disciplines. This work not only offers a comprehensive resource for beginners and expert researchers but also empowers readers to answer strategy-specific research questions, providing actionable insights into NBV planning trends and emerging perspectives.
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