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Open Access Face Recognition by the Construction of Matching Cliques of Points

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This paper addresses the problem of face recognition using a graphical representation to identify structure that is common to pairs of images. Matching graphs are constructed where nodes correspond to local brightness gradient directions and edges are dependent on the relative orientation of the nodes. Similarity is determined from the size of maximal matching cliques in pattern pairs. The method uses a single reference face image to obtain recognition without a training stage. Results on samples from MegaFace obtain a 100% correct recognition result.
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Keywords: Face recognition; graph matching; human vision; pattern recognition; similarity

Document Type: Research Article

Publication date: January 13, 2019

This article was made available online on January 13, 2019 as a Fast Track article with title: "Face recognition by the construction of matching cliques of points".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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