Perspective projection for variance pose face recognition from camera calibration

Fakhir, M. M., Woo, Wai Lok, Chambers, Jonathon and Dlay, Satnam (2016) Perspective projection for variance pose face recognition from camera calibration. In: Optics, Photonics and Digital Technologies for Imaging Applications IV, 5th - 6th April 2016, Brussels, Belgium.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1117/12.2231350

Abstract

Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: 3D, Face recognition, face tracking, intrinsic camera parameters, perspective projection, variance pose
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 09 Apr 2019 10:25
Last Modified: 10 Oct 2019 20:15
URI: http://nrl.northumbria.ac.uk/id/eprint/38854

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