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Authors: Michaela Steinhoff 1 and Daniel Göhring 2

Affiliations: 1 Business Area Intelligent Driving Functions, IAV GmbH, Rockwellstr. 3, 38518 Gifhorn, Germany ; 2 Institute of Computer Science, Freie Universität Berlin, Arnimallee 7, 14195 Berlin, Germany

Keyword(s): Automated Driving, Convolutional Neural Network, Headpose, Pedestrian Intention, Semi-supervision.

Abstract: The challenge of determining pedestrians head poses in camera images is a topic that has already been researched extensively. With the ever-increasing level of automation in the field of Advanced Driver Assistance Systems, a robust head orientation detection is becoming more and more important for pedestrian safety. The fact that this topic is still relevant, however, indicates the complexity of this task. Recently, trained classifiers for discretized head poses have recorded the best results. But large databases, which are essential for an appropriate training of neural networks meeting the special requirements of automatic driving, can hardly be found. Therefore, this paper presents a framework with which reference measurements of head and upper body poses for the generation of training data can be carried out. This data is used to train a convolutional neural network for classifying head and upper body poses. The result is extended in a semi-supervised manner which optimizes and g eneralizes the detector, so that it is applicable to the prediction of pedestrian intention. (More)

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Paper citation in several formats:
Steinhoff, M. and Göhring, D. (2020). Pedestrian Head and Body Pose Estimation with CNN in the Context of Automated Driving. In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-419-0; ISSN 2184-495X, SciTePress, pages 353-360. DOI: 10.5220/0009410903530360

@conference{vehits20,
author={Michaela Steinhoff. and Daniel Göhring.},
title={Pedestrian Head and Body Pose Estimation with CNN in the Context of Automated Driving},
booktitle={Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2020},
pages={353-360},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009410903530360},
isbn={978-989-758-419-0},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Pedestrian Head and Body Pose Estimation with CNN in the Context of Automated Driving
SN - 978-989-758-419-0
IS - 2184-495X
AU - Steinhoff, M.
AU - Göhring, D.
PY - 2020
SP - 353
EP - 360
DO - 10.5220/0009410903530360
PB - SciTePress