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昆虫空间记忆的旋转不变视觉处理

Rotation invariant visual processing for spatial memory in insects.

作者信息

Stone Thomas, Mangan Michael, Wystrach Antoine, Webb Barbara

机构信息

School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.

Sheffield Robotics, Department of Computer Science, University of Sheffield, Regent Court, Sheffield S1 4DP, UK.

出版信息

Interface Focus. 2018 Aug 6;8(4):20180010. doi: 10.1098/rsfs.2018.0010. Epub 2018 Jun 15.

DOI:10.1098/rsfs.2018.0010
PMID:29951190
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6015815/
Abstract

Visual memory is crucial to navigation in many animals, including insects. Here, we focus on the problem of visual homing, that is, using comparison of the view at a current location with a view stored at the home location to control movement towards home by a novel shortcut. Insects show several visual specializations that appear advantageous for this task, including almost panoramic field of view and ultraviolet light sensitivity, which enhances the salience of the skyline. We discuss several proposals for subsequent processing of the image to obtain the required motion information, focusing on how each might deal with the problem of yaw rotation of the current view relative to the home view. Possible solutions include tagging of views with information from the celestial compass system, using multiple views pointing towards home, or rotation invariant encoding of the view. We illustrate briefly how a well-known shape description method from computer vision, Zernike moments, could provide a compact and rotation invariant representation of sky shapes to enhance visual homing. We discuss the biological plausibility of this solution, and also a fourth strategy, based on observed behaviour of insects, that involves transfer of information from visual memory matching to the compass system.

摘要

视觉记忆对于包括昆虫在内的许多动物的导航至关重要。在此,我们聚焦于视觉归巢问题,即通过一种新颖的捷径,将当前位置的视野与存储在归巢位置的视野进行比较,以控制向家的移动。昆虫展现出几种对该任务似乎有利的视觉特化,包括几乎全景的视野和紫外线敏感性,这增强了天际线的显著性。我们讨论了几种对图像进行后续处理以获取所需运动信息的提议,重点关注每种提议如何处理当前视野相对于归巢视野的偏航旋转问题。可能的解决方案包括用来自天体罗盘系统的信息标记视野、使用多个指向家的视野,或对视野进行旋转不变编码。我们简要说明计算机视觉中一种著名的形状描述方法——泽尼克矩,如何能够提供天空形状的紧凑且旋转不变表示,以增强视觉归巢能力。我们讨论了该解决方案的生物学合理性,以及基于观察到的昆虫行为的第四种策略,该策略涉及从视觉记忆匹配向罗盘系统传递信息。

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本文引用的文献

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Unraveling the neural basis of insect navigation.揭示昆虫导航的神经基础。
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Quantifying navigational information: The catchment volumes of panoramic snapshots in outdoor scenes.量化导航信息:室外场景中全景快照的集水量
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Neural coding in the visual system of Drosophila melanogaster: How do small neural populations support visually guided behaviours?黑腹果蝇视觉系统中的神经编码:小型神经群体如何支持视觉引导行为?
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How Ants Use Vision When Homing Backward.蚂蚁如何在向后归巢时使用视觉。
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