Home // ACHI 2023, The Sixteenth International Conference on Advances in Computer-Human Interactions // View article

Lightweight Human Activity Recognition for Ambient Assisted Living

Authors:
Mohamad Reza Shahabian Alashti
Mohammad Hossein Bamorovat Abadi
Patrick Holthaus
Catherine Menon
Farshid Amirabdollahian

Keywords: classification, Multi-view, Skeleton-based, Activity Recognition Pipeline, Assistive Robot

Abstract:
Ambient Assisted Living (AAL) systems aim to improve the safety, comfort, and quality of life for the populations with specific attention given to prolonging personal independence during later stages of life. Human Activity Recognition (HAR) plays a crucial role in enabling AAL systems to recognise and understand human actions. Multi-view human activity recognition (MV-HAR) techniques are particularly useful for AAL systems as they can use information from multiple sensors to capture different perspectives of human activities and can help to improve the robustness and accuracy of activity recognition. In this work, we propose a lightweight activity recognition pipeline that utilizes skeleton data from multiple perspectives with the objective of enhancing an assistive robot's perception of human activity. The pipeline includes data sampling, spatial temporal data transformation, and representation and classification methods. This work contrasts a modified classic LeNet classification model (M-LeNet) versus a Vision Transformer (ViT) in detecting and classifying human activities. Both methods are evaluated using a multi-perspective dataset of human activities in the home (RHM-HAR-SK). Our results indicate that combining camera views can improve recognition accuracy. Furthermore, our pipeline provides an efficient and scalable solution in the AAL context, where bandwidth and computing resources are often limited.

Pages: 188 to 193

Copyright: Copyright (c) IARIA, 2023

Publication date: April 24, 2023

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-68558-078-0

Location: Venice, Italy

Dates: from April 24, 2023 to April 28, 2023