International Journal of Activity and Behavior Computing
Online ISSN : 2759-2871
Introduction of the OpenPack Dataset and Lessons Learned from Organizing OpenPack Challenge 2022
Takuya MaekawaNaoya YoshimuraJaime MoralesTakahiro Hara
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JOURNAL OPEN ACCESS

2024 Volume 2024 Issue 2 Pages 1-21

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Abstract

This study introduces OpenPack, a comprehensive dataset developed for the recognition of packaging work activities. The availability of sensor datasets for recognizing work activities in industrial settings has been constrained due to the challenges in obtaining realistic data, which often requires close cooperation with industrial sites. This limitation has hindered research and development in industrial application methods based on activity recognition. OpenPack comprises 53.8 hours of diverse sensor data, encompassing acceleration data, keypoints, depth images, and readings from IoT devices such as handheld barcode scanners. This data was gathered from 16 participants with varying degrees of experience in packaging work. We apply various human activity recognition models to the dataset and provide future directions of complex work activity recognition studies in the activity recognition community based on the results. In addition, we organized an activity recognition competition, OpenPack Challenge 2022, based on the OpenPack dataset. This paper also intro- duces lessons learned from organizing the competition. The OpenPack dataset is available at https://open-pack.github.io/.

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