Bag-of-Features based Activity Classification using Body-joints Data

Parul Shukla, K.K. Biswas, Prem K. Kalra

2015

Abstract

In this paper, we propose a Bag-of-Joint-Features model for the classification of human actions from body-joints data acquired using depth sensors such as Microsoft Kinect. Our method uses novel scale and translation invariant features in spherical coordinate system extracted from the joints. These features also capture the subtle movements of joints relative to the depth axis. The proposed Bag-of-Joint-Features model uses the well known bag-of-words model in the context of joints for the representation of an action sample. We also propose to augment the Bag-of-Joint-Features model with a Hierarchical Temporal histogram model to take into account the temporal information of the body-joints sequence. Experimental study shows that the augmentation improves the classification accuracy. We test our approach on theMSR-Action3D and Cornell activity datasets using support vector machine.

Paper Citation

in Harvard Style

Shukla P., Biswas K. and Kalra P. (2015). Bag-of-Features based Activity Classification using Body-joints Data . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 314-322. DOI: 10.5220/0005303103140322

in Bibtex Style

@conference{visapp15,
author={Parul Shukla and K.K. Biswas and Prem K. Kalra},
title={Bag-of-Features based Activity Classification using Body-joints Data},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={314-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005303103140322},
isbn={978-989-758-089-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Bag-of-Features based Activity Classification using Body-joints Data
SN - 978-989-758-089-5
AU - Shukla P.
AU - Biswas K.
AU - Kalra P.
PY - 2015
SP - 314
EP - 322
DO - 10.5220/0005303103140322