Method for Identification of Individual Flamingos Based on Movement Logs

Riku Okazaki, Yu Suzuki

Abstract: This research aims to enable non-wearing and non-contact identification of individual animals. As an approach to this goal, we examined the feasibility of an identification method using movement logs, which is one of the animal behaviors. In this study, flamingos kept in a zoo were targeted. In order to collect the movement logs of flamingos, we developed a system in YOLO to identify individual flamingos and record their locations based on videos taken in the zoo's keeping area. In addition, we analyzed the collected movement logs of multiple individuals using a neural network and found that the movement logs could be used to detect individuals with higher identification accuracy than random inference for individual identification. Furthermore, we showed that the location where individuals tend to stay and the posture they tend to adopt change depending on conditions such as weather (rainy or cloudy) and the time of day (noon time period). This research indicates the feasibility of i

External IDs:dblp:conf/icsoft/OkazakiS25