Automatic Fish Tracking: Keeping Track of Who's Who

Author

• Ari Spraggins

Date of Award

2021

Document Type

Dissertation/Thesis

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Fily, Yaouen

Abstract

Automatic video tracking has had a major impact on animal behavior studies. One of the challenges of this technique is keeping track of the identities of the sh, especially when they swim together and exchange positions. In this project we use the python programming language to address this problem for groups of sh. The video data comes from schooling assays performed at FAU's Cave sh Trilab (Dr. Keene, Dr. Duboue, and Dr. Kowalko). The method is inspired by the idTracker animal tracking software: we track patterns of brightness as a visual identi er of each sh which we then use to detect when the sh swap places.

Comments

Thesis (B.A.)--Florida Atlantic University, Harriet L. Wilkes Honors College, 2021

Recommended Citation

Spraggins, Ari, "Automatic Fish Tracking: Keeping Track of Who's Who" (2021). Harriet L Wilkes Honors College Theses 2020 - Present. 126.
https://digitalcommons.fau.edu/etd_honors/126

Extent

26 p.

Identifier

FAUHT00162