Title: Face recognition against pose variations using multi-resolution multiple colour fusion

Authors: Mustafa M. Alrjebi; Wanquan Liu; Ling Li

Addresses: Department of Computing, Curtin University, 6102 WA, Australia ' Department of Computing, Curtin University, 6102 WA, Australia ' Department of Computing, Curtin University, 6102 WA, Australia

Abstract: In this paper we propose a new colour fusion approach called the multi-resolution MCF (MMCF) model. Unlike the recently proposed MCF and 2D_MCF using the colour images with same resolutions, this new model use the colour information of images with different resolutions with an aim to find one optimal combination of different colour combinations of images with different resolutions. More importantly, this new MMCF model can be used to face recognition against pose variations, especially when it is embedded with a deep learning network. Extensive experiments on seven different databases show the superiority of the proposed model over the MCF, 2D_MCF and RGB colour space, especially in the case of large pose variations, the corresponding improvements are significant. This research shed a light of future research on colour face recognition against pose variations.

Keywords: face recognition; colour information utilisation; deep learning; pose variations.

DOI: 10.1504/IJMISSP.2016.085269

International Journal of Machine Intelligence and Sensory Signal Processing, 2016 Vol.1 No.4, pp.304 - 320

Received: 21 Jan 2017
Accepted: 21 Jan 2017
Published online: 19 Jul 2017 *

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