Human Motion Recognition Using TMRIs with Extended HOOF

DOI

10.2991/jrnal.k.201215.004How to use a DOI?

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 Atlantis Press B.V.

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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TY  - JOUR
AU  - Jing Cao
AU  - Youtaro Yamashita
AU  - Joo Kooi Tan
PY  - 2020
DA  - 2020/12/21
TI  - Human Motion Recognition Using TMRIs with Extended HOOF
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 231
EP  - 235
VL  - 7
IS  - 4
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.201215.004
DO  - 10.2991/jrnal.k.201215.004
ID  - Cao2020
ER  -