BossouChimpanzee: Long-term Chimpanzee Video Dataset

2026-10-04

AI Summary

This study addresses the scarcity of long-term behavioral visual data on wild chimpanzees, which constrains both cognitive research and machine learning benchmarking. By integrating collaborative field collection with audiovisual analysis techniques, this work constructs a continuous longitudinal video archive spanning 30 years and exceeding 1,200 hours. It formally introduces the BossouChimpanzee70h dataset, comprising 74 hours of snapshot footage focused on individual and action recognition tasks across 23 target individuals. This contribution effectively bridges the gap in long-term primate behavioral data, providing a high-quality, structured video benchmark resource for animal cognition research, ethical inquiry, and AI model training.

Abstract

We describe the BossouChimpanzee video dataset, a unique long-term visual record of wild chimpanzees at an outdoor laboratory for field experiments in Bossou, Guinea, spanning three decades (1988-2018) and comprising over 1,200 hours of continuous video recordings collected through collaborative fieldwork and research. In this paper, we outline the history and scientific contributions of the experimental paradigm and video archive, provide key statistics and details on the structure of the main video dataset, and release an initial ~74h snapshot, BossouChimpanzee70h, covering 23 identified individuals focused on chimpanzee individual and action recognition, ahead of the full video resource. This dataset represents a valuable resource for cognitive and behavioural research in ethology and a rich benchmark for training and evaluating machine learning models on audiovisual data from the wild.

Problem

• chimpanzee recognition
• action recognition
• long-term video dataset
• wildlife behavior
• machine learning benchmark

Innovation

• Video Dataset
• Individual Recognition
• Action Recognition
• Wild Chimpanzees
• Machine Learning Benchmark