Computer-assisted human annotation for animal identification
Author
Beard, AudreyOther Contributors
Stewart, Charles V.; Su, Hui; Yener, Bülent, 1959-;Date Issued
2020-08Subject
Computer scienceDegree
MS;Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.; Attribution-NonCommercial-NoDerivs 3.0 United StatesMetadata
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Photographic wildlife censusing (PWC) -- in which animals are surveilled by way of photography, entered into a database, and counted -- has historically required significant labor on the part of human annotators, largely due to small and rare well-annotated training datasets. One framework, photographic mark-recapture (or sight-resight), leverages photographs taken by volunteers, scientists, and camera traps, and necessitates the identification of individuals based on visual similarity. State-of-the-art methods for this kind of PWC leverage a detect-classify-rank-verify-annotate pipeline. We focus on the latter three steps in an effort to help spur broader community interest that the other constituent components (detection and classification) have enjoyed for decades. To that end, we formalize the Computer-Assisted Human Annotation (CAHA) problem and explore several metrics and evaluation protocols that indicate algorithmic correctness and expected human labor, including the trade-off between them.;Description
August 2020; School of ScienceDepartment
Dept. of Computer Science;Publisher
Rensselaer Polytechnic Institute, Troy, NYRelationships
Rensselaer Theses and Dissertations Online Collection;Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.;Collections
Except where otherwise noted, this item's license is described as CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.