Exploring of alternative representations of facial images for face recognition

Description and classification of face images is a significant task of computer vision, machine learning and pattern recognition communities. In the past, researchers have made tremendous efforts in this task. Previous researchers always seek high-resolution face images for better image classificati...

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Bibliographic Details
Published in:International journal of machine learning and cybernetics 2020-10, Vol.11 (10), p.2289-2295
Main Authors: Qin, Yongbin, Sun, Lilei, Xu, Yong
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Artificial Intelligence
Classification
Collaboration
Complex Systems
Computational Intelligence
Computer vision
Control
Engineering
Exploitation
Face recognition
Formability
Image classification
Image resolution
Machine learning
Mechatronics
Methods
Original Article
Pattern Recognition
Representations
Robotics
Systems Biology
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Summary:Description and classification of face images is a significant task of computer vision, machine learning and pattern recognition communities. In the past, researchers have made tremendous efforts in this task. Previous researchers always seek high-resolution face images for better image classification. However, with this paper, we present and demonstrate a new opinion that in some cases the use of alternative representations of facial images are very useful for face recognition and properly reducing the image resolution might be beneficial to better classification of face images. This may be attributed to the deformable property of faces and the fact that the proposed alternative representations can in some extent reduce the within-class difference of facial images. Also, the presented idea appear to be useful for helping people to improve face recognition techniques in real worlds.
ISSN:1868-8071
1868-808X
DOI:10.1007/s13042-020-01116-4