Authors
Joo Kooi Tan*, Haruka Egawa
Department of Mechanical and Control Engineering, Kyushu Institute of Technology, Sensuicho 1-1, Tobata, Kitakyushu 804-8550, Japan
*Corresponding author. Email: [email protected]
Corresponding Author
Joo Kooi Tan
Received 23 November 2020, Accepted 23 May 2021, Available Online 24 July 2021.
DOI
https://doi.org/10.2991/jrnal.k.210713.013How to use a DOI?
Keywords
Fallen person detection; head and lower body detection; aerial images; rotation-invariant HOG; rotation-invariant LBP; Random Forest; peak of gradient histograms
Abstract
This paper proposes a method of detecting a person fallen on the ground and its head and lower body from aerial images. The study intends to automate discovering victims of disasters such as earthquakes from areal images taken by an unmanned aerial vehicle (UAV). Rotation-invariant histogram of oriented gradients and rotation-invariant local binary pattern are used as features describing a fallen person so as to detect it regardless of its body orientation. The proposed method also detects the head and the lower body of a fallen person using the peak of the gradient histogram. Experimental results show satisfactory performance of the proposed method.
Copyright
© 2021 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/).