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一个扩展的带注释天光偏振图像数据库,涵盖了两个月的时间。

An extended database of annotated skylight polarization images covering a period of two months.

机构信息

Aix Marseille Univ, CNRS, ISM, Marseille, France.

Stellantis, Velizy-Villacoublay, France.

出版信息

BMC Res Notes. 2024 Oct 14;17(1):306. doi: 10.1186/s13104-024-06959-6.

Abstract

OBJECTIVES

Recent advances in bio-inspired navigation have sparked interest in the phenomenon of skylight polarization. This interest stems from the potential of skylight-based orientation sensors, which performance can be simulated using physical models. However, the effectiveness of machine learning algorithms in this domain relies heavily on access to large datasets for training. Although there are several databases of simulated images in literature, there remains a lack of publicly available annotated real-world color polarimetric images of the sky across various weather conditions.

DATA DESCRIPTION

We present here a dataset obtained from a long-term experimental setup designed to collect polarimetric images from a stand-alone camera. The setup utilizes a Division-of-Focal-Plane polarization camera equipped with a fisheye lens mounted on a rotative telescope mount. Furthermore, we obtained the sensor's orientation within the East-North-Up (ENU) frame from a geometrical calibration and an algorithm provided with the database. To facilitate further research in this area, the present sample dataset spanning two months has been made available on a public archive with manual annotations as required by deep learning algorithms. The images were acquired at 10 min intervals and were taken with various exposure times ranging from 33µs to 300ms.

摘要

目的

生物启发式导航的最新进展引发了人们对天光偏振现象的兴趣。这种兴趣源于基于天光的定向传感器的潜力,其性能可以使用物理模型进行模拟。然而,机器学习算法在该领域的有效性在很大程度上依赖于对大量训练数据的访问。尽管文献中有几个模拟图像数据库,但仍然缺乏可用于各种天气条件下的天空的公开可用标注的真实世界彩色偏振图像。

数据描述

我们在此展示了一个从长期实验设置中获得的数据集,该设置旨在从独立摄像机收集偏振图像。该设置使用配备鱼眼镜头的焦平面分割偏振相机,安装在旋转望远镜架上。此外,我们从几何校准和数据库中提供的算法获得了传感器在东-北-上(ENU)框架中的方位。为了促进该领域的进一步研究,本研究样本数据集跨越两个月,已在公共档案中提供,其中包含深度学习算法所需的手动标注。图像以 10 分钟的间隔采集,曝光时间从 33µs 到 300ms 不等。

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