EventFinder: a program for screening remotely captured images

Camera traps are becoming ubiquitous tools for ecologists. While easily deployed, they require human time to organize, review, and classify images including sequences of images of the same individual, and non-target images triggered by environmental conditions. For such cases, we developed an automa...

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Bibliographic Details
Published in:Environmental monitoring and assessment 2019-06, Vol.191 (6), p.406-10, Article 406
Main Authors: Janzen, Michael, Ritter, Ashley, Walker, Philip D., Visscher, Darcy R.
Format: Article
Language:English
Subjects:
Accuracy
Alberta
Animals
Animals, Wild
Atmospheric Protection/Air Quality Control/Air Pollution
Automation
Cameras
Colour
Computer Peripherals
Computer software
Earth and Environmental Science
Ecologists
Ecology
Ecotoxicology
Environment
Environmental conditions
Environmental Management
Environmental monitoring
Environmental Monitoring - instrumentation
Environmental Monitoring - methods
Environmental science
Histograms
Humans
Image classification
Image Processing, Computer-Assisted - instrumentation
Image Processing, Computer-Assisted - methods
Monitoring systems
Monitoring/Environmental Analysis
Remote Sensing Technology - instrumentation
Remote Sensing Technology - methods
Software
Subtraction
Target recognition
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Summary:Camera traps are becoming ubiquitous tools for ecologists. While easily deployed, they require human time to organize, review, and classify images including sequences of images of the same individual, and non-target images triggered by environmental conditions. For such cases, we developed an automated computer program, named EventFinder, to reduce operator time by pre-processing and classifying images using background subtraction techniques and color histogram comparisons. We tested the accuracy of the program against images previously classified by a human operator. The automated classification, on average, reduced the data requiring human input by 90.8% with an accuracy of 96.1%, and produced a false positive rate of only 3.4%. Thus, EventFinder provides an efficient method for reducing the time for human operators to review and classify images making camera trap projects, which compile a large number of images, less costly to process. Our testing process used medium to large animals, but will also work with smaller animals, provided their images occupy a sufficient area of the frame. While our discussion focuses on camera trap image reduction, we also discuss how EventFinder might be used in conjunction with other software developments for managing camera trap data.
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-019-7518-9