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Recent development in face recognition
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DOI：10.1016/j.neucom.2019.08.110.png)
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Abstract
En 中文
Face stands out as a preferable biometric trait for automatic human authentication as it is intuitive and non-intrusive. This paper investigates various feature-based automatic face recognition approaches in detail. High degree of freedom in head movement and human emotion leads a face recognition system to face critical challenges in terms of pose, illumination and expression. Human face also undergoes irreversible changes due to aging. These factors makes the process of face recognition non trivial and hard. This paper also provides a review of the facial recognition approaches individually dealing with these issues. Applications of face recognition in the forensic domain sometimes needs identification using a scanned facial image. The scenario is quite useful to get investigative leads. Important approaches for the same are also been discussed in the manuscript. Recent developments in the low-cost image capturing devices has flooded the facial image databases with a lot of images, at the same time availability of GPU based compute power has helped develop deep learning approaches to handle the face recognition at a very accurate and massive level. The same has also been surveyed and analyzed in the manuscript. (c) 2020 Elsevier B.V. All rights reserved.
Keywords:
Biometrics
Face recognition
Digital face
Scanned face
Face features
Deep learning
Indexing schemes
Journal
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6.5
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2.5W
Citations:
6.5W
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