Title: Face analysis in video: face detection and tracking with pose estimation

Authors: Hazar Mliki; Mohamed Hammami

Addresses: MIRACL-ENET'COM, University of Sfax, 3018 Sfax, Tunisia ' MIRACL-FSS, University of Sfax, 3018 Sfax, Tunisia

Abstract: We introduced a full automatic approach to achieve face detection and tracking with pose estimation in video sequences. The proposed approach consists of three modules: face detection module, face tracking module and face pose estimation module. A combination between detection and tracking modules was performed to overcome the different challenging problems that might occur while detecting or tracking faces. Afterward face pose estimation module was applied to select the best camera capture which is closest to the frontal face view for better face recognition task. The performance of these modules was evaluated with an experimental study which has proven the robustness of the proposed approach for a face analysis in video.

Keywords: face detection; face tracking; face pose estimation; data-mining; SVM; adaboost.

DOI: 10.1504/IJBM.2018.091625

International Journal of Biometrics, 2018 Vol.10 No.2, pp.121 - 141

Received: 01 Jul 2017
Accepted: 15 Dec 2017

Published online: 08 May 2018 *

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