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An Unconstrained Face Detection Algorithm Based on Visual Saliency

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Advances in Internetworking, Data & Web Technologies (EIDWT 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 6))

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Abstract

This paper a novel face detection method based on visual saliency mechanism to improve the accuracy of unconstrained face recognition. Log Gabor transformation is used to extract visual features, and obtain facial saliency map by using stable balance measurement method based on Graph-Based Visual Saliency. Then binary image is obtained by segmenting facial saliency map with maximum entropy threshold and the rectangle area is marked by setting the centroid of object region as the center. Face region is detected from the original image according to the rectangle area. Experimental results on LFW database show that our algorithm can effectively remove the background interference without losing any face information and quickly precisely detect the face region which is more conducive to the unconstrained face recognition.

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Acknowledgement

This work is financially supported by NSFC Projects No. 61471162, Program of International science and technology cooperation (0S2015ZR1083), NSF of Jiangsu Province (BK20141389, BK20160781), NSF of Hubei Province (2014CFB589), Technology Research Program of Hubei Provincial Department of Education (D20141406), Key Laboratory of meteorological detection and information processing in Jiangsu Province (KDXS1503), and NIT fund for Young Scholar (CKJB201602).

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Authors and Affiliations

  1. Department of Communication Engineering, Nanjing Institute of Technology, Nanjing, 211167, China

    Ying Tong, Rui Chen & Liangbao Jiao

  2. Jiangsu Province Traditional Chinese Medicine Hospital, Nanjing, 210000, China

    Yu Yan

Authors
  1. Ying Tong
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  2. Rui Chen
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  3. Liangbao Jiao
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  4. Yu Yan
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Corresponding author

Correspondence to Rui Chen .

Editor information

Editors and Affiliations

  1. Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. School of Computer Sciences, Hubei University of Technology, Wuhan, China

    Mingwu Zhang

  3. Department of Electronic Technology, Key, Engineering University of CAPF, Xi’an, Xizang, China

    Xu An Wang

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Tong, Y., Chen, R., Jiao, L., Yan, Y. (2018). An Unconstrained Face Detection Algorithm Based on Visual Saliency. In: Barolli, L., Zhang, M., Wang, X. (eds) Advances in Internetworking, Data & Web Technologies. EIDWT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-59463-7_46

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  • DOI: https://doi.org/10.1007/978-3-319-59463-7_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59462-0

  • Online ISBN: 978-3-319-59463-7

  • eBook Packages: EngineeringEngineering (R0)

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