3D Point Cloud Descriptor for Posture Recognition

Margarita Khokhlova, Cyrille Migniot, Albert Dipanda

2018

Abstract

This paper introduces a simple yet powerful algorithm for global human posture description based on 3D Point Cloud data. The proposed algorithm preserves spatial contextual information about a 3D object in a video sequence and can be used as an intermediate step in human-motion related Computer Vision applications such as action recognition, gait analysis, human-computer interaction. The proposed descriptor captures a point cloud structure by means of a modified 3D regular grid and a corresponding cells space occupancy information. The performance of our method was evaluated on the task of posture recognition and automatic action segmentation.

Paper Citation

in Harvard Style

Khokhlova M., Migniot C. and Dipanda A. (2018). 3D Point Cloud Descriptor for Posture Recognition. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP; ISBN 978-989-758-290-5, SciTePress, pages 161-168. DOI: 10.5220/0006541801610168

in Bibtex Style

@conference{visapp18,
author={Margarita Khokhlova and Cyrille Migniot and Albert Dipanda},
title={3D Point Cloud Descriptor for Posture Recognition},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP},
year={2018},
pages={161-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006541801610168},
isbn={978-989-758-290-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP
TI - 3D Point Cloud Descriptor for Posture Recognition
SN - 978-989-758-290-5
AU - Khokhlova M.
AU - Migniot C.
AU - Dipanda A.
PY - 2018
SP - 161
EP - 168
DO - 10.5220/0006541801610168
PB - SciTePress