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Authors: Christian Hofmann ; Florian Particke ; Markus Hiller and Jörn Thielecke

Affiliation: Department of Electrical, Electronic and Communication Engineering, Information Technology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Am Wolfsmantel 33, Erlangen, Germany

ISBN: 978-989-758-354-4

Keyword(s): Object Detection, Infrastructural Cameras, Stereo Vision, Deep Learning, Autonomous Driving, Robotics.

Abstract: In the future, autonomously driving vehicles have to navigate in challenging environments. In some situations, their perception capabilities are not able to generate a reliable overview of the environment, by reason of occlusions. In this contribution, an infrastructural stereo camera system for environment perception is proposed. Similar existing systems only detect moving objects by background subtraction algorithms and monocular cameras. In contrast, the proposed approach fuses three different algorithms for object detection and classification and uses stereo vision for object localization. The algorithmic concept is composed of a background subtraction algorithm based on Gaussian Mixture Models, the convolutional neural network ”You only look once” as well as a novel algorithm for detecting salient objects in depth maps. The combination of these complementary object detection principles allows the reliable detection of dynamic as well as static objects. An algorithm for fusing the results of the three object detection methods based on bounding boxes is introduced. The proposed fusion algorithm for bounding boxes improves the detection results and provides an information fusion. We evaluate the proposed concept on real word data. The object detection, classification and localization in the real world scenario is investigated and discussed. (More)

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Paper citation in several formats:
Hofmann, C.; Particke, F.; Hiller, M. and Thielecke, J. (2019). Object Detection, Classification and Localization by Infrastructural Stereo Cameras.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 808-815. DOI: 10.5220/0007370408080815

@conference{visapp19,
author={Christian Hofmann. and Florian Particke. and Markus Hiller. and Jörn Thielecke.},
title={Object Detection, Classification and Localization by Infrastructural Stereo Cameras},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={808-815},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007370408080815},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Object Detection, Classification and Localization by Infrastructural Stereo Cameras
SN - 978-989-758-354-4
AU - Hofmann, C.
AU - Particke, F.
AU - Hiller, M.
AU - Thielecke, J.
PY - 2019
SP - 808
EP - 815
DO - 10.5220/0007370408080815

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