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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Main Authors: Saul Greenberg, Theresa Godin, Jesse Whittington
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:Ecology and Evolution
Subjects:
Online Access:https://doi.org/10.1002/ece3.5767
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spelling 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
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