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ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
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CNKI
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5%
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Impact Factor 2022: 1.0
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Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
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Home
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2020
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Volume 11, No. 2, May 2020
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A Dynamic Unconstrained Feature Matching Algorithm for Face Recognition
Ganesh G. Patil
1
and Rohitash K. Banyal
2
1. Department of Computer Science and Engineering, SVERI’s College of Engineering, Pandharpur, India
2. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India
Abstract
—Since the last three decades, face detection and recognition have become very active and a huge part of image processing research. Front view/direction face recognition has proved promising results with many constraints. In real-world applications like video surveillance, missing investigation, front views cannot be guaranteed as input. Hence the failure rates can degrade the performance of the face recognition system. In this paper, a new partial face recognition system proposed. It is used to overcome the drawbacks of the face recognition system, which based on the front view detection and recognition system. This partial face recognition can also be termed as Unconstrained Dynamic Feature Matching (U-DFM); it does not require prior knowledge of angle, direction, and view. The U-DFM method combines Fully Convolutional Networks (FCNs) and Ambiguity Sensitive Matching Classifier (AMC). The U-DFM addresses various face sizes problem of partial face recognition. The algorithm will be testing with CASIA-NIR-Mobile, LFW, and CAISA-NIR-Distance databases and will prove better results than traditional algorithms.
Index Terms
—unconstrained dynamic feature matching, fully convolutional network, ambiguity sensitive matching classifier partial face recognition
Cite: Ganesh G. Patil and Rohitash K. Banyal, "A Dynamic Unconstrained Feature Matching Algorithm for Face Recognition," Journal of Advances in Information Technology, Vol. 11, No. 2, pp. 103-108, May 2020. doi: 10.12720/jait.11.2.103-108
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
10-NT031-India
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