Design patterns for wildlife‐related camera trap image analysis
Abstract This paper describes and explains design patterns for software that supports how analysts can efficiently inspect and classify camera trap images for wildlife‐related ecological attributes. Broadly speaking, a design pattern identifies a commonly occurring problem and a general reusable des...
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Online Access: | https://doi.org/10.1002/ece3.5767 |
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doaj-5b9acf9de1104eafb47f57d9a9de31b02021-03-02T06:40:53ZengWileyEcology and Evolution2045-77582019-12-01924137061373010.1002/ece3.5767Design patterns for wildlife‐related camera trap image analysisSaul Greenberg0Theresa Godin1Jesse Whittington2Department of Computer Science University of Calgary Calgary AB CanadaFreshwater Fisheries Society of BC Research Evaluation & Development Section University of British Columbia Vancouver BC CanadaParks Canada, Banff National Park Banff AB CanadaAbstract This paper describes and explains design patterns for software that supports how analysts can efficiently inspect and classify camera trap images for wildlife‐related ecological attributes. Broadly speaking, a design pattern identifies a commonly occurring problem and a general reusable design approach to solve that problem. A developer can then use that design approach to create a specific software solution appropriate to the particular situation under consideration. In particular, design patterns for camera trap image analysis by wildlife biologists address solutions to commonly occurring problems they face while inspecting a large number of images and entering ecological data describing image attributes. We developed design patterns for image classification based on our understanding of biologists' needs that we acquired over 8 years during development and application of the freely available Timelapse image analysis system. For each design pattern presented, we describe the problem, a design approach that solves that problem, and a concrete example of how Timelapse addresses the design pattern. Our design patterns offer both general and specific solutions related to: maintaining data consistency, efficiencies in image inspection, methods for navigating between images, efficiencies in data entry including highly repetitious data entry, and sorting and filtering image into sequences, episodes, and subsets. These design patterns can inform the design of other camera trap systems and can help biologists assess how competing software products address their project‐specific needs along with determining an efficient workflow.https://doi.org/10.1002/ece3.5767camera trapsdata encoding and acquisitiondesign patternsexperience designhuman–computer interactionimage inspection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Saul Greenberg Theresa Godin Jesse Whittington |
spellingShingle |
Saul Greenberg Theresa Godin Jesse Whittington Design patterns for wildlife‐related camera trap image analysis Ecology and Evolution camera traps data encoding and acquisition design patterns experience design human–computer interaction image inspection |
author_facet |
Saul Greenberg Theresa Godin Jesse Whittington |
author_sort |
Saul Greenberg |
title |
Design patterns for wildlife‐related camera trap image analysis |
title_short |
Design patterns for wildlife‐related camera trap image analysis |
title_full |
Design patterns for wildlife‐related camera trap image analysis |
title_fullStr |
Design patterns for wildlife‐related camera trap image analysis |
title_full_unstemmed |
Design patterns for wildlife‐related camera trap image analysis |
title_sort |
design patterns for wildlife‐related camera trap image analysis |
publisher |
Wiley |
series |
Ecology and Evolution |
issn |
2045-7758 |
publishDate |
2019-12-01 |
description |
Abstract This paper describes and explains design patterns for software that supports how analysts can efficiently inspect and classify camera trap images for wildlife‐related ecological attributes. Broadly speaking, a design pattern identifies a commonly occurring problem and a general reusable design approach to solve that problem. A developer can then use that design approach to create a specific software solution appropriate to the particular situation under consideration. In particular, design patterns for camera trap image analysis by wildlife biologists address solutions to commonly occurring problems they face while inspecting a large number of images and entering ecological data describing image attributes. We developed design patterns for image classification based on our understanding of biologists' needs that we acquired over 8 years during development and application of the freely available Timelapse image analysis system. For each design pattern presented, we describe the problem, a design approach that solves that problem, and a concrete example of how Timelapse addresses the design pattern. Our design patterns offer both general and specific solutions related to: maintaining data consistency, efficiencies in image inspection, methods for navigating between images, efficiencies in data entry including highly repetitious data entry, and sorting and filtering image into sequences, episodes, and subsets. These design patterns can inform the design of other camera trap systems and can help biologists assess how competing software products address their project‐specific needs along with determining an efficient workflow. |
topic |
camera traps data encoding and acquisition design patterns experience design human–computer interaction image inspection |
url |
https://doi.org/10.1002/ece3.5767 |
work_keys_str_mv |
AT saulgreenberg designpatternsforwildliferelatedcameratrapimageanalysis AT theresagodin designpatternsforwildliferelatedcameratrapimageanalysis AT jessewhittington designpatternsforwildliferelatedcameratrapimageanalysis |
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