低光照条件和动态场景下建筑工地的自监督单目深度估计

IF 9.6 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Jie Shen, Ziyi Huang, Lang Jiao
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引用次数: 0

摘要

从单张图像中估计建筑场景深度对于各种下游任务至关重要。自监督单目深度估算方法最近取得了令人瞩目的成果,展示了最先进的性能。然而,建筑工地的低照度条件和动态场景给这些方法带来了巨大挑战,阻碍了它们的实际应用。因此,本文提出了一种名为 LLD-Depth 的架构来应对这些挑战,其中包括一种改进的 ForkGAN 模型,用于从晴天图像生成成对的弱光图像;一种新的统一学习方法,用于准确估计单目深度、运动流、摄像机自我运动及其内在参数;以及一种训练框架,用于在弱光和晴天条件下有效估计单目深度。最后,在建筑场景中验证了单目深度估计的有效性。LLD-Depth 在晴天和弱光场景下的相对平均误差分别增加了 16.67% 和 20.17%,平均阶次精度分别增加了 2.60% 和 1.80%,达到了最先进的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-supervised monocular depth estimation on construction sites in low-light conditions and dynamic scenes
Estimating construction scene depth from a single image is crucial for various downstream tasks. Self-supervised monocular depth estimation methods have recently achieved impressive results and demonstrated state-of-the-art performance. However, the low-light conditions and dynamic scenes on construction sites pose significant challenges to these methods, hindering their practical deployment. Therefore, an architecture called LLD-Depth is presented to address these challenges, including an improved ForkGAN model to generate paired low-light images from clear-day images, a new unifying learning method for accurately estimating monocular depth, motion flow, camera ego-motion, and its intrinsic parameters, as well as a training framework to estimate monocular depth under both low-light and clear-day conditions effectively. Finally, the effectiveness of monocular depth estimation in construction scenes is verified. LLD-Depth brings 16.67% and 20.17% gain in relative mean error for clear-day and low-light scenes and 2.60% and 1.80% gain in average order accuracy, achieving state-of-the-art performance.
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来源期刊
Automation in Construction
Automation in Construction 工程技术-工程:土木
CiteScore
19.20
自引率
16.50%
发文量
563
审稿时长
8.5 months
期刊介绍: Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities. The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.
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