LDA Combined Depth Similarity and Gradient Features for Human Detection using a Time-of-Flight Sensor

Alexandros Gavriilidis, Carsten Stahlschmidt, Jörg Velten, Anton Kummert

2015

Abstract

Visual object detection is an important task for many research areas like driver assistance systems (DASs), industrial automation and various safety applications with human interaction. Since detection of pedestrians is a growing research area, different kinds of visual methods and sensors have been introduced to overcome this problem. This paper introduces new relational depth similarity features (RDSF) for the pedestrian detection using a Time-of-Flight (ToF) camera sensor. The new features are based on mean, variance, skewness and kurtosis values of local regions inside the depth image generated by the Time-of-Flight sensor. An evaluation between these new features, already existing relational depth similarity features using depth histograms of local regions and the well known histogram of oriented gradients (HOGs), which deliver very good results in the topic of pedestrian detection, will be presented. To incorporate more dimensional feature spaces, an existing AdaBoost algorithm, which uses linear discriminant analysis (LDA) for feature space reduction and new combination of already extracted features in the training procedure, will be presented too.

Paper Citation

in Harvard Style

Gavriilidis A., Stahlschmidt C., Velten J. and Kummert A. (2015). LDA Combined Depth Similarity and Gradient Features for Human Detection using a Time-of-Flight Sensor . 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 349-356. DOI: 10.5220/0005257403490356

in Bibtex Style

@conference{visapp15,
author={Alexandros Gavriilidis and Carsten Stahlschmidt and Jörg Velten and Anton Kummert},
title={LDA Combined Depth Similarity and Gradient Features for Human Detection using a Time-of-Flight Sensor},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={349-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005257403490356},
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 - LDA Combined Depth Similarity and Gradient Features for Human Detection using a Time-of-Flight Sensor
SN - 978-989-758-089-5
AU - Gavriilidis A.
AU - Stahlschmidt C.
AU - Velten J.
AU - Kummert A.
PY - 2015
SP - 349
EP - 356
DO - 10.5220/0005257403490356