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Article

A Cognitively-Motivated Framework for Partial Face Recognition in Unconstrained Scenarios

INESC TEC and Faculdade de Engenharia, Universidade do Porto, Campus da FEUP, Rua Dr. Roberto Frias, n 378, 4200-465 Porto, Portugal
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Sensors 2015, 15(1), 1903-1924; https://doi.org/10.3390/s150101903
Received: 24 November 2014 / Accepted: 7 January 2015 / Published: 16 January 2015
(This article belongs to the Section Physical Sensors)
Humans perform and rely on face recognition routinely and effortlessly throughout their daily lives. Multiple works in recent years have sought to replicate this process in a robust and automatic way. However, it is known that the performance of face recognition algorithms is severely compromised in non-ideal image acquisition scenarios. In an attempt to deal with conditions, such as occlusion and heterogeneous illumination, we propose a new approach motivated by the global precedent hypothesis of the human brain’s cognitive mechanisms of perception. An automatic modeling of SIFT keypoint descriptors using a Gaussian mixture model (GMM)-based universal background model method is proposed. A decision is, then, made in an innovative hierarchical sense, with holistic information gaining precedence over a more detailed local analysis. The algorithm was tested on the ORL, ARand Extended Yale B Face databases and presented state-of-the-art performance for a variety of experimental setups. View Full-Text
Keywords: biometrics; face recognition; partial data; universal background model; Gaussian mixture models biometrics; face recognition; partial data; universal background model; Gaussian mixture models
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MDPI and ACS Style

Monteiro, J.C.; Cardoso, J.S. A Cognitively-Motivated Framework for Partial Face Recognition in Unconstrained Scenarios. Sensors 2015, 15, 1903-1924. https://doi.org/10.3390/s150101903

AMA Style

Monteiro JC, Cardoso JS. A Cognitively-Motivated Framework for Partial Face Recognition in Unconstrained Scenarios. Sensors. 2015; 15(1):1903-1924. https://doi.org/10.3390/s150101903

Chicago/Turabian Style

Monteiro, João C., and Jaime S. Cardoso. 2015. "A Cognitively-Motivated Framework for Partial Face Recognition in Unconstrained Scenarios" Sensors 15, no. 1: 1903-1924. https://doi.org/10.3390/s150101903

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