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Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 35, Number 11(4) (2023)
Copyright(C) MYU K.K.
pp. 3927-3945
S&M3460 Research Paper of Special Issue
https://doi.org/10.18494/SAM4501
Published: November 30, 2023

Detecting Eating Behavior of Elephants in a Zoo Using Temporal Action Localization [PDF]

Ken Nishioka, Wataru Noguchi, Hiroyuki Izuka, and Masahito Yamamoto

(Received May 8, 2023; Accepted October 3, 2023)

Keywords: animal behavior recognition, temporal action localization, zoo, elephants

The behavioral observation of animals in zoos is indispensable for their health management and the improvement of their breeding environment. However, the day-to-day recording of animal behaviors is time-consuming for zookeepers. Hence, we aim to automatically generate animal behavioral observation reports, called “ethograms,” in cooperation with the Sapporo Maruyama Zoo. While studies using contact sensors [e.g., accelerometers, global positioning system (GPS) , and radio frequency identification (RFID)] have had some success in zoos, noncontact sensors (e.g., cameras and microphones) tend to be avoided because of frequent occlusion and the need for nighttime detection. However, noncontact sensors are preferable to contact sensors owing to animal welfare concerns. Here, we propose a method for automatic elephant behavior recognition based on elephant tracking information using video from surveillance cameras. In particular, we focus only on “eating,” which is difficult to detect accurately because it requires relatively long-term observation. Therefore, we solve the problem by using a method based on temporal action localization (TAL), which is a task of predicting when and where a target action is performed over a relatively lengthy period. The TAL method has been applied mainly to humans and less to animals. In our experiments, the average precision of eating behavior detection using TAL was 0.853. The results show that TAL is also effective in animal behavior recognition.

Corresponding author: Ken Nishioka


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Cite this article
Ken Nishioka, Wataru Noguchi, Hiroyuki Izuka, and Masahito Yamamoto, Detecting Eating Behavior of Elephants in a Zoo Using Temporal Action Localization, Sens. Mater., Vol. 35, No. 11, 2023, p. 3927-3945.



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