Visual Recognition of Great Ape Behaviours in the Wild

Faizaan Sakib, Tilo Burghardt

Research output: Contribution to conferenceConference Paperpeer-review

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Abstract

Whilst species detection and individual identification of great apes have previously been attempted with success, research into automated behaviour recognition remains a humancentric task. In this paper we present a first great ape-specific visual behaviour recognition system and related data annotations for detecting core ape behaviours. Among others, these include sitting, walking, and climbing. The presented basic dual-stream model with late fusion is capable of performing multi-subject multi-behaviour recognition on apes in challenging camera trap footage. More than 180,000 frames across 500 videos from the PanAfrican dataset were annotated with individual IDs and
behaviour labels to end-to-end train and evaluate the system. In summary, our key contributions include a proposed system capable of an accuracy of 73.52%, along with the behaviour annotated dataset, key code and network weights.
Original languageEnglish
Publication statusPublished - 15 Jan 2021
Event International Conference on Pattern Recognition (ICPR) Workshop on Visual Observation and Analysis of Vertebrate And Insect Behavior - Milan, Italy
Duration: 10 Jan 202115 Jan 2021
Conference number: 25
https://www.micc.unifi.it/icpr2020/

Conference

Conference International Conference on Pattern Recognition (ICPR) Workshop on Visual Observation and Analysis of Vertebrate And Insect Behavior
Abbreviated titleVAIB
CountryItaly
CityMilan
Period10/01/2115/01/21
Internet address

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