@inproceedings{ad174f7e4e2b41c59cccb0af5e146262,
title = "Generic face detection and pose estimation algorithm suitable for the face de-identification problem",
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.",
keywords = "Classifier fusion, De-identification, Logistic regression, Nonfrontal face detection, Pose estimation, SVM",
author = "Aleksandar Milchevski and Dijana Petrovska-Delacr{\'e}taz and Dejan Gjorgjevikj",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 7th International Conference on Information and Communication Technologies, ICT 2015 ; Conference date: 01-10-2015 Through 04-10-2015",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-25733-4\_23",
language = "English",
isbn = "9783319257310",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "225--234",
editor = "Suzana Loshkovska and Saso Koceski",
booktitle = "ICT Innovations 2015",
}