Shady dealings: Robust, long-term visual localisation using illumination invariance
Shady dealings: Robust, long-term visual localisation using illumination invariance
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DOI：
10.1109/icra.2014.6906961
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
C. McManus;W. Churchill;William P. Maddern;Alexander D. Stewart;P. Newman
中科院分区：
文献类型：
--
作者：
C. McManus;W. Churchill;William P. Maddern;Alexander D. Stewart;P. Newman
本文是关于使用立体视觉扩展户外定位的范围和耐久性。定位的核心是发现记录图像和实时图像之间的特征对应关系的基本任务。这个问题的一个方面涉及决定在哪里寻找图像中的对应关系，第二个方面是决定寻找什么。这后一点，这是我们的论文的主要重点，需要了解如何以及为什么视觉特征的外观可以随着时间的推移而变化。特别是，这些知识使我们能够更好地处理照明中的突然和具有挑战性的变化。我们展示了如何通过实例化一个并行的图像处理流，它对光照不变的图像进行操作，我们可以大大提高户外视觉导航系统的性能。我们将演示，解释和分析RGB到光照不变变换的效果，并建议以很少的成本，它成为那些关心机器人在户外长时间运行的人的可行工具。
This paper is about extending the reach and endurance of outdoor localisation using stereo vision. At the heart of the localisation is the fundamental task of discovering feature correspondences between recorded and live images. One aspect of this problem involves deciding where to look for correspondences in an image and the second is deciding what to look for. This latter point, which is the main focus of our paper, requires understanding how and why the appearance of visual features can change over time. In particular, such knowledge allows us to better deal with abrupt and challenging changes in lighting. We show how by instantiating a parallel image processing stream which operates on illumination-invariant images, we can substantially improve the performance of an outdoor visual navigation system. We will demonstrate, explain and analyse the effect of the RGB to illumination-invariant transformation and suggest that for little cost it becomes a viable tool for those concerned with having robots operate for long periods outdoors.