Image segmentation for appearance-based self-localisation

P. Zingaretti, L. Bossoletti
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引用次数: 3

Abstract

The paper describes a segmentation technique that well fits to an appearance-based self-localisation. In an appearance-based approach robot positioning is performed without using explicit object models. The choice of the representation of image appearances is fundamental. We use image-domain features, as opposed to interpreted characteristics of the scene, and we adopt feature vectors including both the chromatic attributes of colour sets and their mutual spatial relationships. To obtain the colour sets we perform image segmentation by autothresholding the colour histograms and taking into account what the results are addressed to. The experimental results indicate that the method performs well for a variety of environments.
基于外观的自定位图像分割
本文描述了一种非常适合基于外观的自定位的分割技术。在基于外观的方法中,无需使用显式对象模型即可执行机器人定位。图像表象的选择是最根本的。我们使用图像域特征,而不是场景的解释特征,我们采用包括颜色集的颜色属性及其相互空间关系的特征向量。为了获得颜色集,我们通过对颜色直方图进行自动阈值分割并考虑到结果的目的来执行图像分割。实验结果表明,该方法适用于多种环境。
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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