Action recognition based on binocular vision

DOI

10.2991/jrnal.2017.4.1.2How to use a DOI?

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 Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Yiwei Ru
AU  - Hongyue Du
AU  - Shuxiao Li
AU  - Hongxing Chang
PY  - 2017
DA  - 2017/06/01
TI  - Action recognition based on binocular vision
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 5
EP  - 9
VL  - 4
IS  - 1
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2017.4.1.2
DO  - 10.2991/jrnal.2017.4.1.2
ID  - Ru2017
ER  -