Skip to main content

Generic Face Detection and Pose Estimation Algorithm Suitable for the Face De-identification Problem

  • Conference paper
  • First Online:
Book cover ICT Innovations 2015 (ICT Innovations 2015)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 399))

Included in the following conference series:

  • 1080 Accesses

Abstract

In this work we tackle the problem of face de-identification in an image. The first step towards a solution to this problem is the design of a successful generic face detection algorithm, which will detect all of the faces in the image or video, regardless of the pose. If the face detection algorithm fails to detect even one face, the effect of the de-identification algorithm could be neutralized. That is why a novel face detection algorithm is proposed for face detection and pose estimation. The algorithm uses an ensemble of three linear SVM classifiers. The first, second and the third SVM classifier estimate the pitch, yaw and roll angle of the face and a logistic regression is used to combine the results and output a final decision. Second, the results of the face detection and a simple space variant de-identification algorithm are used to show the benefits of simultaneous face detection and face de-identification.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aleksandar Milchevski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Milchevski, A., Petrovska-Delacrétaz, D., Gjorgjevikj, D. (2016). Generic Face Detection and Pose Estimation Algorithm Suitable for the Face De-identification Problem. In: Loshkovska, S., Koceski, S. (eds) ICT Innovations 2015 . ICT Innovations 2015. Advances in Intelligent Systems and Computing, vol 399. Springer, Cham. https://doi.org/10.1007/978-3-319-25733-4_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25733-4_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25731-0

  • Online ISBN: 978-3-319-25733-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics