Action Recognition using the Rf Transform on Optical Flow Images

Josep Maria Carmona, Joan Climent

2017

Abstract

The objective of this paper is the automatic recognition of human actions in video sequences. The use of spatio-temporal features for action recognition has become very popular in recent literature Instead of extracting the spatio-temporal features from the raw video sequence, some authors propose to project the sequence to a single template first. As a contribution we propose the use of several variants of the R transform for projecting the image sequences to templates. The R transform projects the whole sequence to a single image, retaining information concerning movement direction and magnitude. Spatio-temporal features are extracted from the template, they are combined using a bag of words paradigm, and finally fed to a SVM for action classification. The method presented is shown to improve the state-of-art results on the standard Weizmann action dataset

Paper Citation

in Harvard Style

Carmona J. and Climent J. (2017). Action Recognition using the Rf Transform on Optical Flow Images . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 266-271. DOI: 10.5220/0006218002660271

in Bibtex Style

@conference{visapp17,
author={Josep Maria Carmona and Joan Climent},
title={Action Recognition using the Rf Transform on Optical Flow Images},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={266-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006218002660271},
isbn={978-989-758-225-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Action Recognition using the Rf Transform on Optical Flow Images
SN - 978-989-758-225-7
AU - Carmona J.
AU - Climent J.
PY - 2017
SP - 266
EP - 271
DO - 10.5220/0006218002660271