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Authors: Rémi Emonet 1 ; E. Oberzaucher 2 and J.-M. Odobez 3

Affiliations: 1 Université Jean Monnet, France ; 2 University of Vienna, Austria ; 3 Idiap Research Institute, Switzerland

ISBN: 978-989-758-004-8

ISSN: 2184-4321

Keyword(s): Stream Selection, Camera Network, Probabilistic Models, Temporal Topic Models.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Camera Networks and Vision ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Motion, Tracking and Stereo Vision ; Video Surveillance and Event Detection ; Visual Attention and Image Saliency

Abstract: The installation of surveillance networks has been growing exponentially in the last decade. In practice, videos from large surveillance networks are almost never watched, and it is frequent to see surveillance video wall monitors showing empty scenes. There is thus a need to design methods to continuously select streams to be shown to human operators. This paper addresses this issue and make three main contributions: it introduces and investigates, for the first time in the literature, the live stream selection task; based on the theory of social attention, it formalizes a way of obtaining some ground truth for the task and hence a way of evaluating stream selection algorithms; and finally, it proposes a two-step approach to solve this task and compares different approaches for interestingness rating using our framework. Experiments conducted on 9 cameras from a metro station and 5 hours of data randomly selected over one week show that, while complex unsupervised activity modeling a lgorithms achieve good performance, simpler approaches based on amount of motion perform almost as well for this type of indoor setting. (More)

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Paper citation in several formats:
Emonet, R.; Oberzaucher, E. and Odobez, J. (2014). What to Show? - Automatic Stream Selection among Multiple Sensors.In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, ISSN 2184-4321, pages 433-440. DOI: 10.5220/0004688504330440

@conference{visapp14,
author={Rémi Emonet. and E. Oberzaucher. and J.{-}M. Odobez.},
title={What to Show? - Automatic Stream Selection among Multiple Sensors},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={433-440},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004688504330440},
isbn={978-989-758-004-8},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - What to Show? - Automatic Stream Selection among Multiple Sensors
SN - 978-989-758-004-8
AU - Emonet, R.
AU - Oberzaucher, E.
AU - Odobez, J.
PY - 2014
SP - 433
EP - 440
DO - 10.5220/0004688504330440

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