Recognizing faces prone to occlusions and common variations using optimal face subgraphs

An intuitive graph optimization face recognition approach called Harmony Search Oriented-EBGM (HSO-EBGM) inspired by the classical Elastic Bunch Graph Matching (EBGM) graphical model is proposed in this contribution. In the proposed HSO-EBGM, a recent evolutionary approach called harmony search opti...

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Bibliographic Details
Published in:Applied mathematics and computation 2016-06, Vol.283, p.316-332
Main Authors: Lahasan, Badr Mohammed, Venkat, Ibrahim, Al-Betar, Mohammed Azmi, Lutfi, Syaheerah Lebai, Wilde, Philippe De
Format: Article
Language:English
Subjects:
Automation
Evolutionary
Face recognition
Graphical model
Harmony search
Landmarks
Mathematical models
Occlusion
Optimization
Searching
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Summary:An intuitive graph optimization face recognition approach called Harmony Search Oriented-EBGM (HSO-EBGM) inspired by the classical Elastic Bunch Graph Matching (EBGM) graphical model is proposed in this contribution. In the proposed HSO-EBGM, a recent evolutionary approach called harmony search optimization is tailored to automatically determine optimal facial landmarks. A novel notion of face subgraphs have been formulated with the aid of these automated landmarks that maximizes the similarity entailed by the subgraphs. For experimental evaluation, two sets of de facto databases (i.e., AR and Face Recognition Grand Challenge (FRGC) ver2.0) are used to validate and analyze the behavior of the proposed HSO-EBGM in terms of number of subgraphs, varying occlusion sizes, face images under controlled/ideal conditions, realistic partial occlusions, expression variations and varying illumination conditions. For a number of experiments, results justify that the HSO-EBGM shows improved recognition performance when compared to recent state-of-the-art face recognition approaches.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2016.02.047