Building Synthetic Simulated Environments for Configuring and Training Multi-camera Systems for Surveillance Applications

Nerea Aranjuelo, Nerea Aranjuelo, Jorge García, Luis Unzueta, Sara García, Unai Elordi, Unai Elordi, Oihana Otaegui

Abstract

Synthetic simulated environments are gaining popularity in the Deep Learning Era, as they can alleviate the effort and cost of two critical tasks to build multi-camera systems for surveillance applications: setting up the camera system to cover the use cases and generating the labeled dataset to train the required Deep Neural Networks (DNNs). However, there are no simulated environments ready to solve them for all kind of scenarios and use cases. Typically, ‘ad hoc’ environments are built, which cannot be easily applied to other contexts. In this work we present a methodology to build synthetic simulated environments with sufficient generality to be usable in different contexts, with little effort. Our methodology tackles the challenges of the appropriate parameterization of scene configurations, the strategies to generate randomly a wide and balanced range of situations of interest for training DNNs with synthetic data, and the quick image capturing from virtual cameras considering the rendering bottlenecks. We show a practical implementation example for the detection of incorrectly placed luggage in aircraft cabins, including the qualitative and quantitative analysis of the data generation process and its influence in a DNN training, and the required modifications to adapt it to other surveillance contexts.

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Paper Citation


in Harvard Style

Aranjuelo N., García J., Unzueta L., García S., Elordi U. and Otaegui O. (2021). Building Synthetic Simulated Environments for Configuring and Training Multi-camera Systems for Surveillance Applications.In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-488-6, pages 80-91. DOI: 10.5220/0010232400800091


in Bibtex Style

@conference{visapp21,
author={Nerea Aranjuelo and Jorge García and Luis Unzueta and Sara García and Unai Elordi and Oihana Otaegui},
title={Building Synthetic Simulated Environments for Configuring and Training Multi-camera Systems for Surveillance Applications},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2021},
pages={80-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010232400800091},
isbn={978-989-758-488-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Building Synthetic Simulated Environments for Configuring and Training Multi-camera Systems for Surveillance Applications
SN - 978-989-758-488-6
AU - Aranjuelo N.
AU - García J.
AU - Unzueta L.
AU - García S.
AU - Elordi U.
AU - Otaegui O.
PY - 2021
SP - 80
EP - 91
DO - 10.5220/0010232400800091