Penn, Matthew J;
Miles, Verity;
Astley, Kelly L;
Ham, Cally;
Woodroffe, Rosie;
Rowcliffe, Marcus;
Donnelly, Christl A;
(2024)
Sherlock—A flexible, low-resource tool for processing camera-trapping images.
Methods in Ecology and Evolution
, 15
(1)
pp. 91-102.
10.1111/2041-210X.14254.
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Abstract
1. The use of camera traps to study wildlife has increased markedly in the last two decades. Camera surveys typically produce large data sets which require processing to isolate images containing the species of interest. This is time consuming and costly, particularly if there are many empty images that can result from false triggers. Computer vision technology can assist with data processing, but existing artificial intelligence algorithms are limited by the requirement of a training data set, which itself can be challenging to acquire. Furthermore, deep-learning methods often require powerful hardware and proficient coding skills. 2. We present Sherlock, a novel algorithm that can reduce the time required to process camera trap data by removing a large number of unwanted images. The code is adaptable, simple to use and requires minimal processing power. 3. We tested Sherlock on 240,596 camera trap images collected from 46 cameras placed in a range of habitats on farms in Cornwall, United Kingdom, and set the parameters to find European badgers (Meles meles). The algorithm correctly classified 91.9% of badger images and removed 49.3% of the unwanted ‘empty’ images. When testing model parameters, we found that faster processing times were achieved by reducing both the number of sampled pixels and ‘bouncing’ attempts (the number of paths explored to identify a disturbance), with minimal implications for model sensitivity and specificity. When Sherlock was tested on two sites which contained no livestock in their images, its performance greatly improved and it removed 92.3% of the empty images. 4. Although further refinements may improve its performance, Sherlock is currently an accessible, simple and useful tool for processing camera trap data.
| Type: | Article |
|---|---|
| Title: | Sherlock—A flexible, low-resource tool for processing camera-trapping images |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/2041-210X.14254 |
| Publisher version: | https://doi.org/10.1111/2041-210X.14254 |
| Language: | English |
| Additional information: | Copyright © 2023 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Camera-trapping, image classification |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10178032 |
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