A computer vision for animal ecology. (29th November 2017)

• Record Type: Journal Article
• Authors: Weinstein, Ben G.
• Editors: Prugh, Laura
• Is Part Of: Journal of animal ecology. Volume 87:Number 3(2018:May)
• Page Start: 533
• Page End: 545
• Publication Date: 2017-11-29
• Subjects: automation -- camera traps -- ecological monitoring -- images -- unmanned aerial vehicles; Animal ecology -- Periodicals; 591.7
• DOI: 10.1111/1365-2656.12780
• Languages: English
• ISSNs: 0021-8790

Abstract

Abstract: A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck. Computer vision can greatly increase the efficiency, repeatability and accuracy of image review. Computer vision uses image features, such as colour, shape and texture to infer image content. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting and identity tasks. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis. Abstract : Ecologists are increasingly using image capture to bolster data collection. However, reviewing these images remains a bottleneck. Computer vision can increase the accuracy and efficiency of image review. The author outlines the goals, tools and applications of ecological computer vision to animal ecology.