access icon free Human-level face verification with intra-personal factor analysis and deep face representation

© The Institution of Engineering and Technology
Received 21/03/2017, Accepted 30/01/2018, Revised 22/01/2018, Published 09/02/2018

The last two decades have seen an escalating interest in methods for large-scale unconstrained face recognition. While the promise of computer vision systems to efficiently and accurately verify and identify faces in naturally occurring circumstances still remains elusive, recent advances in deep learning are taking us closer to human-level recognition. In this study, the authors propose a new paradigm which employs deep features in a feature extractor and intra-personal factor analysis as a recogniser. The proposed new strategy represents the face changes of a person using identity specific components and the intra-personal variation through reinterpretation of a Bayesian generative factor analysis model. The authors employ the expectation-maximisation algorithm to calculate model parameters which cannot be observed directly. Recognition outcomes achieved through benchmarking on large-scale wild databases, Labeled Faces in the Wild (LFW) and Youtube Face (YTF), clearly prove that the proposed approach provides remarkable face verification performance improvement over state-of-the-art approaches.

Inspec keywords: expectation-maximisation algorithm; feature extraction; Bayes methods; face recognition; learning (artificial intelligence); computer vision; image representation

Other keywords: human-level face verification; large-scale unconstrained face recognition; deep learning; feature extractor; computer vision systems; human-level recognition; Labeled face recognition; intra-personal variation; deep features; deep face representation; remarkable face verification performance improvement; intrapersonal factor analysis; Youtube face recognition; recognition outcomes

Subjects: Other topics in statistics; Image recognition; Computer vision and image processing techniques; Other topics in statistics

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