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Classification of Imagery Data and Face Recognition Techniques

by Neeraj Pratap, Shwetank, Vikesh Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 10
Year of Publication: 2014
Authors: Neeraj Pratap, Shwetank, Vikesh Kumar
10.5120/14876-3272

Neeraj Pratap, Shwetank, Vikesh Kumar . Classification of Imagery Data and Face Recognition Techniques. International Journal of Computer Applications. 85, 10 ( January 2014), 21-26. DOI=10.5120/14876-3272

@article{ 10.5120/14876-3272,
author = { Neeraj Pratap, Shwetank, Vikesh Kumar },
title = { Classification of Imagery Data and Face Recognition Techniques },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 10 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 21-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number10/14876-3272/ },
doi = { 10.5120/14876-3272 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:02:05.298751+05:30
%A Neeraj Pratap
%A Shwetank
%A Vikesh Kumar
%T Classification of Imagery Data and Face Recognition Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 10
%P 21-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A lot of research work has been done by the researchers in the field of face recognition. These days many innovative issues of research and application in the field of face recognition are still pending and required to be discuss and develop. Different studies on face recognition already have been done and implemented but suffering from a single view point, applications and methods, because of traditional imagery input data. This paper explores and classifies the different input imagery data: traditional images, videos (sequence of images with time interval) and 3D images, considered to develop the face recognition techniques: signal processing, machine learning and multidimensional face recognition. The key feature of this study is to introduce a new era of face recognition system and technology (input sources, effects, techniques, assessment, limitations etc. ) based on Multidimensional Imagery Data known as Multidimensional Face Recognition System (MFRS).

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Index Terms

Computer Science
Information Sciences

Keywords

Face Recognition Sensory Inputs Manifold learning Hyperspectral Image

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