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Human Face Pose Estimation based on Feature Extraction Points

by Guneet Bhullar, Vikram Mutneja
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 9
Year of Publication: 2016
Authors: Guneet Bhullar, Vikram Mutneja
10.5120/ijca2016909922

Guneet Bhullar, Vikram Mutneja . Human Face Pose Estimation based on Feature Extraction Points. International Journal of Computer Applications. 142, 9 ( May 2016), 41-43. DOI=10.5120/ijca2016909922

@article{ 10.5120/ijca2016909922,
author = { Guneet Bhullar, Vikram Mutneja },
title = { Human Face Pose Estimation based on Feature Extraction Points },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 9 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 41-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number9/24928-2016909922/ },
doi = { 10.5120/ijca2016909922 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:34.655792+05:30
%A Guneet Bhullar
%A Vikram Mutneja
%T Human Face Pose Estimation based on Feature Extraction Points
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 9
%P 41-43
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The process of Face Recognition comprises of Face Detection, feature extraction and verification or identification. The extraction and identification are stages in the FR process. Many face recognition algorithms have been developed. This has resulted in development of manifold robust techniques such as background removal, illumination normalization and others which support the algorithm to withstand the undesirable effects and improve the success rate. This paper provides a survey and method for face pose estimation. This method is based on feature extraction points of two different face poses and then matched points between these two face poses will give the results. This method is one of the simplest methods for low resolution images.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction low resolution roll pitch yaw orientation.

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