Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm

Noel Perez, Sérgio Faria, Miguel Coimbra

Abstract

In this paper we study the energy saving potential of smart scale selection methods when using the Viola and Jones face detector running on smartphone devices. Our motivation is that cloud and edge-cloud multi-user environments may provide enough contextual information to create this type of scale selection algorithms. Given their non-trivial design, we must first inspect its actual benefits, before committing important research resources to actually produce relevant smart scale selection methods. Our experimental methodology in this paper assumes the optimum scenario of a perfect selection of scales for each image (drawn from ground truth annotation, using well-known public datasets), comparing it with the typical multi-scale geometrical progression approach of the Viola Jones algorithm, measuring both classification precision and recall, as well as algorithmic execution time and battery consumption on Android smartphone devices. Results show that if we manage to approximate this perfect scale selection, we obtain very significant energy savings, motivating a strong research investment on this topic.

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Paper Citation


in Harvard Style

Perez N., Faria S. and Coimbra M. (2017). Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING, (BIOSTEC 2017) ISBN 978-989-758-215-8, pages 122-127. DOI: 10.5220/0006247501220127


in Bibtex Style

@conference{bioimaging17,
author={Noel Perez and Sérgio Faria and Miguel Coimbra},
title={Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING, (BIOSTEC 2017)},
year={2017},
pages={122-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006247501220127},
isbn={978-989-758-215-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING, (BIOSTEC 2017)
TI - Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm
SN - 978-989-758-215-8
AU - Perez N.
AU - Faria S.
AU - Coimbra M.
PY - 2017
SP - 122
EP - 127
DO - 10.5220/0006247501220127