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Low complexity hybrid holistic – landmark based approach for face recognition

Modern Face Recognition (FR) systems have to cope with high intra-class variability. Face is a 3D object with wide variability in appearances from each pose. This, along with other causes like luminance variation, becomes one of the main reasons for the high variability. While incremental learning i...

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Published in:Multimedia tools and applications 2021-08, Vol.80 (20), p.30199-30212
Main Authors: Asad, Muhammad, Hussain, Ayyaz, Mir, Usama
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Language:English
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description Modern Face Recognition (FR) systems have to cope with high intra-class variability. Face is a 3D object with wide variability in appearances from each pose. This, along with other causes like luminance variation, becomes one of the main reasons for the high variability. While incremental learning is an unsuited approach for most scenarios, techniques proposed to deal with this issue are often of enormous complexity during training phase and require computational power during operation that is scarcely credible for compact devices. This paper proposes a novel technique where pose specific classification system has been used to attain better classification with low computational cost. State of the art performance measures have been used to assess the validity. Results demonstrate the effectiveness of our pose specific classification system.
doi_str_mv 10.1007/s11042-020-08872-z
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subjects Classification
Complexity
Computer Communication Networks
Computer Science
Computing costs
Data Structures and Information Theory
Deep learning
Distance learning
Face recognition
Facial recognition technology
Multimedia
Multimedia Information Systems
Special Purpose and Application-Based Systems
Variability
title Low complexity hybrid holistic – landmark based approach for face recognition
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