Human Motion Recognition Using TMRIs with Extended HOOF

Authors
Jing Cao1, Youtaro Yamashita1, Joo Kooi Tan2, *
1Graduate School of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
2Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
*Corresponding author. Email: [email protected]
Corresponding Author
Joo Kooi Tan
Received 10 November 2019, Accepted 17 June 2020, Available Online 21 December 2020.
DOI
https://doi.org/10.2991/jrnal.k.201215.004
Keywords
Human motion; description; recognition; elderly care; crime prevention; MHI; triplet motion representation images; HOOF
Abstract
In recent years, research on computer vision has shown great advancement and has been applied to a wide range of fields. Among them, automatic recognition of human motion is an important technology especially in crime prevention and elderly watching systems. Considering this trend, the paper proposes a novel method of human motion description and recognition using a motion history image-based method called triplet motion representation images and an extended feature descriptor called histograms of oriented optical flow which contains information on the direction and velocity of movement. One of the advantages of the proposed method over existent methods is that it solves a self-occlusive motion problem particularly in the depth direction which occurs when a single camera is used. The performance and effectiveness of the proposed method are verified by experiments.
Copyright
© 2020 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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