Bento Packaging Activity Recognition Based on Statistical Features

Conference paper


Rakib Sayem, F., Sheikh, M. M. and Ahad, M. 2022. Bento Packaging Activity Recognition Based on Statistical Features. 3rd International Conference on Activity and Behavior Computing (ABC 2021). Online 22 - 23 Oct 2021 Springer Singapore. https://doi.org/10.1007/978-981-19-0361-8_13
AuthorsRakib Sayem, F., Sheikh, M. M. and Ahad, M.
TypeConference paper
Abstract

Due to the fast advancements of low-cost micro-embedded sensors and MoCap sensors, human action recognition has become an essential study topic and is garnering a lot of interest in different sectors. Recently, it is drawing a lot of attention in human-robot collaboration to assist human to preform regular tasks step-wise because it is difficult to obtain human labor at a lower wage to monitor industrial works. In this work, we have presented a straightforward machine learning paradigm to recognize ten different Bento (lunch-box) packaging activities in real-time world. Unlike other skeleton-based human activity recognition domain, it is a very challenging task due to the absence of lower-body marker information. Under these circumstances, we have provided an in-depth statistical analysis of different Bento packaging activities. After feature extraction process, we have used several machine algorithms and obtained best results in random forest classifier using hyperparameter tuning. We have achieved 64.9% validation accuracy using leave-one-out method.

Year2022
Conference3rd International Conference on Activity and Behavior Computing (ABC 2021)
PublisherSpringer Singapore
Publication dates
Online04 May 2022
Publication process dates
Deposited26 Jul 2023
Journal citationpp. 207-216
ISSN2190-3018
Book titleSensor- and Video-Based Activity and Behavior Computing: Proceedings of 3rd International Conference on Activity and Behavior Computing (ABC 2021)
Book editorAhad, M.
Inoue, S.
Roggen, D.
Fujinami, K.
ISBN9789811903601
9789811903618
Digital Object Identifier (DOI)https://doi.org/10.1007/978-981-19-0361-8_13
Web address (URL) of conference proceedingshttps://link.springer.com/book/10.1007/978-981-19-0361-8
Copyright holder© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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