非朗伯表面及其对视觉 SLAM 的挑战

Sara Pyykölä;Niclas Joswig;Laura Ruotsalainen
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引用次数: 0

摘要

非朗伯表面是一种特殊的表面,会产生被称为 "镜面反射 "的特殊反射率,这给工业 SLAM 带来了潜在的问题。本文回顾了与非朗伯表面研究相关的基本表面反射模型、现代最先进的计算机视觉算法和两个公共数据集(KITTI 和 DiLiGenT)。文章介绍了一个新的数据集 SPINS,用于研究导航中的非朗伯表面,并使用 ResNeXt-101-WSL、ORB SLAM 3 和 TartanVO 对数据进行了实证性能评估。文章最后讨论了实证评估结果和调查结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-Lambertian Surfaces and Their Challenges for Visual SLAM
Non-Lambertian surfaces are special surfaces that can cause specific type of reflectances called specularities, which pose a potential issue in industrial SLAM. This article reviews fundamental surface reflectance models, modern state-of-the-art computer vision algorithms and two public datasets, KITTI and DiLiGenT, related to non-Lambertian surfaces' research. A new dataset, SPINS, is presented for the purpose of studying non-Lambertian surfaces in navigation and an empirical performance evaluation with ResNeXt-101-WSL, ORB SLAM 3 and TartanVO is performed on the data. The article concludes with discussion about the results of empirical evaluation and the findings of the survey.
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