Convolutional Neural Network for Detection and Classification with Event-based Data

Joubert Damien, Konik Hubert, Chausse Frederic

2019

Abstract

Mainly inspired by biological perception systems, event-based sensors provide data with many advantages such as timing precision, data compression and low energy consumption. In this work, it is analyzed how these data can be used to detect and classify cars, in the case of front camera automotive applications. The basic idea is to merge state of the art deep learning algorithms with event-based data integrated into artificial frames. When this preprocessing method is used in viewing purposes, it suggests that the shape of the targets can be extracted, but only when the relative speed is high enough between the camera and the targets. Event-based sensors seems to provide a more robust description of the target’s trajectory than using conventional frames, the object only being described by its moving edges, and independently of lighting conditions. It is also highlighted how features trained on conventional greylevel images can be transferred to event-based data to efficiently detect car into pseudo images.

Paper Citation

in Harvard Style

Damien J., Hubert K. and Frederic C. (2019). Convolutional Neural Network for Detection and Classification with Event-based Data. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 200-208. DOI: 10.5220/0007257002000208

in Bibtex Style

@conference{visapp19,
author={Joubert Damien and Konik Hubert and Chausse Frederic},
title={Convolutional Neural Network for Detection and Classification with Event-based Data},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={200-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007257002000208},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Convolutional Neural Network for Detection and Classification with Event-based Data
SN - 978-989-758-354-4
AU - Damien J.
AU - Hubert K.
AU - Frederic C.
PY - 2019
SP - 200
EP - 208
DO - 10.5220/0007257002000208
PB - SciTePress