Paper
15 October 2012 Face recognition in real uncontrolled environment with correlation filters
Susana Garduño-Massieu, Vitaly Kober
Author Affiliations +
Abstract
Face recognition is a task that humans perform daily and effortlessly. In pattern recognition and computer vision, there has been an increasing interest in automatic face recognition over the past years. Facial recognition systems face challenging problems owing to inherent variations of some factors at image acquisition, such as nonuniform illumination, pose changes, occlusion and ageing. Numerous techniques were proposed for face recognition in still images. Despite recent achievements in this area, the problem of a reliable facial recognition in a real uncontrolled scene still remains open. This work introduces an algorithm that is based on composite correlation filters and does not require prior face segmentation. Optimal filters with respect to the discrimination capability criterion are derived and used to synthesize a single composite filter that can be used for distortion invariant face recognition. Computer simulation results obtained with the suggested algorithm are presented and discussed.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Susana Garduño-Massieu and Vitaly Kober "Face recognition in real uncontrolled environment with correlation filters", Proc. SPIE 8499, Applications of Digital Image Processing XXXV, 849928 (15 October 2012); https://doi.org/10.1117/12.928680
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Cited by 1 scholarly publication.
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KEYWORDS
Image filtering

Facial recognition systems

Detection and tracking algorithms

Digital filtering

Image segmentation

Composites

Linear filtering

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