Cross-context Analysis for Long-term View-point Invariant Person Re-identification via Soft-biometrics using Depth Sensor

Athira Nambiar, Alexandre Bernardino, Jacinto. C. Nascimento

2018

Abstract

We propose a novel methodology for cross-context analysis in person re-identification using 3D features acquired from consumer grade depth sensors. Such features, although theoretically invariant to perspective changes, are nevertheless immersed in noise that depends on the view point, mainly due to the low depth resolution of these sensors and imperfections in skeleton reconstruction algorithms. Thus, the re-identification of persons observed on different poses requires the analysis of the features that transfer well its characteristics between view-points. Taking view-point as context, we propose a cross-context methodology to improve the re-identification of persons on different view-points. On the contrary to 2D cross-view re-identification methods, our approach is based on 3D features that do not require an explicit mapping between view-points, but nevertheless take advantage of feature selection methods that improve the re-identification accuracy.

Paper Citation

in Harvard Style

Nambiar A., Bernardino A. and Nascimento J. (2018). Cross-context Analysis for Long-term View-point Invariant Person Re-identification via Soft-biometrics using Depth Sensor. 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 105-113. DOI: 10.5220/0006620601050113

in Bibtex Style

@conference{visapp18,
author={Athira Nambiar and Alexandre Bernardino and Jacinto. C. Nascimento},
title={Cross-context Analysis for Long-term View-point Invariant Person Re-identification via Soft-biometrics using Depth Sensor},
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={105-113},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006620601050113},
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 - Cross-context Analysis for Long-term View-point Invariant Person Re-identification via Soft-biometrics using Depth Sensor
SN - 978-989-758-290-5
AU - Nambiar A.
AU - Bernardino A.
AU - Nascimento J.
PY - 2018
SP - 105
EP - 113
DO - 10.5220/0006620601050113
PB - SciTePress