Image Compensation for Improving Extraction of Driver’s Facial Features

Jung-Ming Wang, Han-Ping Chou, Sei-Wang Chen, Chiou-Shann Fuh


Extracting driver’s facial feature helps to identify the vigilance level of a driver. Some research about facial feature extraction also has been developed for controlled interface of vehicle. To acquire facial feature of drivers, research using various visual sensors have been reported. However, potential challenges to such a work include rapid illumination variation resulting from ambient lights, abrupt lighting change (e.g., entering/exiting tunnels and sunshine/shadow), and partial occlusion. In this paper, we propose an image compensation method for improve extraction of a driver’s facial features. This method has the advantages of fast processing and high adaptation. Our experiments show that the extraction of driver’s facial features can be improved significantly.


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Paper Citation

in Harvard Style

Wang J., Chou H., Chen S. and Fuh C. (2014). Image Compensation for Improving Extraction of Driver’s Facial Features . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 329-338. DOI: 10.5220/0004690003290338

in Bibtex Style

author={Jung-Ming Wang and Han-Ping Chou and Sei-Wang Chen and Chiou-Shann Fuh},
title={Image Compensation for Improving Extraction of Driver’s Facial Features},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},

in EndNote Style

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Image Compensation for Improving Extraction of Driver’s Facial Features
SN - 978-989-758-003-1
AU - Wang J.
AU - Chou H.
AU - Chen S.
AU - Fuh C.
PY - 2014
SP - 329
EP - 338
DO - 10.5220/0004690003290338