Place recognition of 3D landmarks based on geometric relations

Dario Lodi Rizzini
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引用次数: 17

Abstract

Place recognition based on landmarks or features is an important problem occurring in localization, mapping, computer vision and point cloud processing. In this paper, we present GLAROT-3D, a translation and rotation invariant 3D signature based on geometric relations. The proposed method encodes into a histogram the pairwise relative positions of keypoint features extracted from 3D sensor data. Since it relies only on geometric properties and not on specific feature descriptors, it does not require any prior training or vocabulary construction and enables lightweight comparisons between landmark maps. The similarity of two point maps is computed as the distance between the corresponding rotated histograms to achieve rotation invariance. Histogram rotation is enabled by efficient orientation histogram based on sphere cubical projection. The performance of GLAROT has been assessed through experiments with standard benchmark datasets.
基于几何关系的三维地标位置识别
基于地标或特征的位置识别是定位、地图绘制、计算机视觉和点云处理等领域的重要问题。本文提出了一种基于几何关系的平移和旋转不变性三维签名方法——GLAROT-3D。该方法将从三维传感器数据中提取的关键点特征的成对相对位置编码成直方图。由于它只依赖于几何属性,而不依赖于特定的特征描述符,因此它不需要任何事先的训练或词汇构建,并且可以在地标地图之间进行轻量级比较。两个点图的相似度计算为对应的旋转直方图之间的距离,以实现旋转不变性。直方图旋转是通过基于球立方投影的高效方向直方图实现的。通过标准基准数据集的实验,对该算法的性能进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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