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3D Object Recognition Based on Point Clouds in Underwater Environment with Global Descriptors: A Survey

机译：具有全局描述符的水下环境中基于点云的3D对象识别：一项调查

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摘要

This paper addresses the problem of object recognition from colorless 3D point clouds in underwater environments. It presents a performance comparison of state-of-the-art global descriptors, which are readily available as open source code. The studied methods are intended to assist Autonomous Underwater Vehicles (AUVs) in performing autonomous interventions in underwater Inspection, Maintenance and Repair (IMR) applications. A set of test objects were chosen as being representative of IMR applications whose shape is typically known a priori. As such, CAD models were used to create virtual views of the objects under realistic conditions of added noise and varying resolution. Extensive experiments were conducted from both virtual scans and from real data collected with an AUV equipped with a fast laser sensor developed in our research centre. The underwater testing was conducted from a moving platform, which can create deformations in the perceived shape of the objects. These effects are considerably more difficult to correct than in above-water counterparts, and therefore may affect the performance of the descriptor. Among other conclusions, the testing we conducted illustrated the importance of matching the resolution of the database scans and test scans, as this significantly impacted the performance of all descriptors except one. This paper contributes to the state-of-the-art as being the first work on the comparison and performance evaluation of methods for underwater object recognition. It is also the first effort using comparison of methods for data acquired with a free floating underwater platform.
机译：本文解决了水下环境中从无色3D点云中识别物体的问题。它提供了最新的全局描述符的性能比较，这些描述符可以作为开放源代码轻松获得。研究的方法旨在协助自动水下航行器（AUV）在水下检查，维护和修理（IMR）应用中执行自主干预。选择一组测试对象来代表IMR应用程序，这些应用程序的形状通常是先验的。因此，在增加噪声和变化分辨率的实际条件下，CAD模型用于创建对象的虚拟视图。我们使用研究中心开发的配备有快速激光传感器的AUV从虚拟扫描和实际数据中进行了广泛的实验。水下测试是在移动平台上进行的，该平台会在物体的感知形状上产生变形。这些影响比水上的对应物更难纠正，因此可能影响描述符的性能。除其他结论外，我们进行的测试说明了匹配数据库扫描和测试扫描的分辨率的重要性，因为这会显着影响除一个描述符之外的所有描述符的性能。本文作为最新技术，是水下物体识别方法的比较和性能评估的第一项工作。这也是通过比较使用自由浮动水下平台获取的数据的方法进行的首次尝试。

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