Coarse to Fine Training for Low-Resolution Heterogeneous Face Recognition

Mudunuri, SP and Biswas, S (2018) Coarse to Fine Training for Low-Resolution Heterogeneous Face Recognition. In: 25th IEEE International Conference on Image Processing, ICIP 2018, 7 - 10 October 2018, Athens; Greece, pp. 2421-2425.

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Abstract

Recently, near-infrared (NIR) images are being increasingly used for recognizing facial images across illumination variations and in low-light conditions. In surveillance scenarios, the captured NIR may have low-resolution which results in significant loss of discriminative information along with uncontrolled pose. In this work, we address the challenging task of matching these low-resolution (LR) uncontrolled NIR images with high-resolution (HR) controlled visible (VIS) images usually present in the database. Since the probe and gallery images differ significantly in terms of pose, resolution and spectral properties, we employ a two-stage approach. First, the images are transformed into a common space using metric learning such that the images of the same subject are pushed closer and those of different subjects are pushed apart. We then define an objective function which can simultaneously push both LR NIR and HR VIS samples towards the centroids of the HR VIS samples. We show that the approach is general and can be used for other data like RGB-D and also for matching across pose. Extensive experiments conducted on five datasets shows the effectiveness of our approach. © 2018 IEEE.

Item Type:	Conference Paper
Publication:	Proceedings - International Conference on Image Processing, ICIP
Publisher:	IEEE Computer Society
Additional Information:	Copyright for this article belongs to IEEE Computer Society.
Keywords:	Infrared devices, Illumination variation; Low light conditions; Low resolution; Objective functions; Pose; Spectral properties; Super resolution; Two stage approach, Face recognition
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	06 May 2019 12:42
Last Modified:	06 May 2019 12:42
URI:	http://eprints.iisc.ac.in/id/eprint/62119

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