Spatio-temporal feature points detection and extraction based on convolutional neural network

DOI

10.2991/icecee-15.2015.83How to use a DOI?

Keywords

Spatio-temporal feature points detection and extraction based on convolutional neural network

Abstract

Convolutional neural network is a kind of deep learning model, but it only act on a single image generally. This paper expands the convolutional neural network, studies common spatio-temporal features detection and extraction algorithm, proposes a model for detecting and extracting spatio-temporal features based on convolutional neural network, applicates convolutional neural network in action recognition. This model use a plurality of consecutive video frames as input, extract image feature and time dimension information from sequent video frames, convolute and sub sampling alternately, extract a variety of advanced complex abstract features gradually. Experiments show that spatio-temporal convolution neural network has improved ability to classifing and learning.

Copyright

© 2015, 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  - CONF
AU  - Chaoyu Yang
AU  - Qian Liu
AU  - Yincheng Liang
PY  - 2015/06
DA  - 2015/06
TI  - Spatio-temporal feature points detection and extraction based on convolutional neural network
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 400
EP  - 403
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.83
DO  - 10.2991/icecee-15.2015.83
ID  - Yang2015/06
ER  -