Continuous Driver Activity Recognition from Short Isolated Action Sequences

Patrick Weyers, Anton Kummert

2021

Abstract

Advanced driver monitoring systems significantly increase safety by detecting driver drowsiness or distraction. Knowing the driver’s current state or actions allows for adaptive warning strategies or prediction of the driver’s response time to take back the control of a semi-autonomous vehicle. We present an online driver monitoring system for detecting characteristic actions and states inside a car interior by analysing the full driver seat region. With the proposed training method, a recurrent neural network for online sequence analysis is capable of learning from isolated action sequences only. The proposed method allows training of a recurrent neural network from snippets of actions, while this network can be applied to continuous video streams at runtime. With a mean average precision of 0.77, we reach better classification results on our test data than commonly used methods.

Paper Citation

in Harvard Style

Weyers P. and Kummert A. (2021). Continuous Driver Activity Recognition from Short Isolated Action Sequences.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 158-165. DOI: 10.5220/0010185501580165

in Bibtex Style

@conference{icpram21,
author={Patrick Weyers and Anton Kummert},
title={Continuous Driver Activity Recognition from Short Isolated Action Sequences},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={158-165},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010185501580165},
isbn={978-989-758-486-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Continuous Driver Activity Recognition from Short Isolated Action Sequences
SN - 978-989-758-486-2
AU - Weyers P.
AU - Kummert A.
PY - 2021
SP - 158
EP - 165
DO - 10.5220/0010185501580165