Authors
Yiwei Ru, Hongyue Du, Shuxiao Li, Hongxing Chang
Corresponding Author
Yiwei Ru
Available Online 1 June 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.1.2
Keywords
action recognition; binocular version; convolutional neural networks; motion
history image;
Abstract
Aimed at the problem that the recognition accuracy of the monocular camera
is low, we propose a binocular vision recognition algorithm for action
recognition based on HART-Net(Human action recognition networks).Firstly,
the left and right views obtained by the binocular camera are matched to
obtain the depth map of the human body. Then, the depth information is
projected onto the three planes, the projection images of three directions
are used to construct MHI (motion history image), and are combined into
a new image. Finally, we use HART-Net to train a classifier for action
recognition. Experimental results show that the binocular recognition algorithm
is 18% more accurate than the monocular recognition algorithm.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).