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来自 Zooniverse 企鹅观察项目的延时图像和志愿者分类。

Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project.

机构信息

Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK.

Zooniverse, Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, UK.

出版信息

Sci Data. 2018 Jun 26;5:180124. doi: 10.1038/sdata.2018.124.

Abstract

Automated time-lapse cameras can facilitate reliable and consistent monitoring of wild animal populations. In this report, data from 73,802 images taken by 15 different Penguin Watch cameras are presented, capturing the dynamics of penguin (Spheniscidae; Pygoscelis spp.) breeding colonies across the Antarctic Peninsula, South Shetland Islands and South Georgia (03/2012 to 01/2014). Citizen science provides a means by which large and otherwise intractable photographic data sets can be processed, and here we describe the methodology associated with the Zooniverse project Penguin Watch, and provide validation of the method. We present anonymised volunteer classifications for the 73,802 images, alongside the associated metadata (including date/time and temperature information). In addition to the benefits for ecological monitoring, such as easy detection of animal attendance patterns, this type of annotated time-lapse imagery can be employed as a training tool for machine learning algorithms to automate data extraction, and we encourage the use of this data set for computer vision development.

摘要

自动延时摄像机可以方便可靠地监测野生动物种群。本报告介绍了在南极半岛、南设得兰群岛和南乔治亚岛(2012 年 3 月至 2014 年 1 月)使用 15 台不同的 Penguin Watch 摄像机拍摄的 73802 张图像的数据,这些图像捕捉了企鹅(企鹅科;Pygoscelis spp.)繁殖群体的动态。公民科学为处理大型且难以处理的摄影数据集提供了一种手段,在这里,我们描述了与 Zooniverse 项目 Penguin Watch 相关的方法,并对该方法进行了验证。我们提供了 73802 张图像的匿名志愿者分类,以及相关元数据(包括日期/时间和温度信息)。除了对生态监测有好处,例如可以轻松检测动物出勤模式之外,这种注释的延时图像还可以用作机器学习算法的训练工具,以实现数据自动提取,我们鼓励将此数据集用于计算机视觉开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1a5/6018656/96a982002fdd/sdata2018124-f1.jpg

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