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An Investigation on Face Detection Applications

by Mohammad Almasi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 21
Year of Publication: 2019
Authors: Mohammad Almasi
10.5120/ijca2019919664

Mohammad Almasi . An Investigation on Face Detection Applications. International Journal of Computer Applications. 177, 21 ( Dec 2019), 17-23. DOI=10.5120/ijca2019919664

@article{ 10.5120/ijca2019919664,
author = { Mohammad Almasi },
title = { An Investigation on Face Detection Applications },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 21 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number21/31020-2019919664/ },
doi = { 10.5120/ijca2019919664 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:29.969946+05:30
%A Mohammad Almasi
%T An Investigation on Face Detection Applications
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 21
%P 17-23
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face detection in uncontrolled ambiance continues to be a challenge to traditional face detection methods due to the large difference in facial expressions. The task of alignment is particularly difficult when the face comes from an extremely unconditional environment. To overcome these problems, the present paper is a reliable and deeply considerable application that allows users to detect a face(s) in real-time and process them. Database of faces with bounding rectangles and facial landmark locations is collected, and simple discriminative classifiers are learned from each of them. Then methods for morphing, warping, swapping and averaging of faces are presented. As a result, faces can be very effectively detected, aligned/ oriented and used for the above methods. In addition, based on results this approach can detect faces and eyes in difficult conditions without explicitly simulating their variation. Evaluating the tests of the application, it can confidently said that this face detection method is accurate and effective and reaches the most modern level of performance. The same methodology can easily be generalized to other tasks, as well as the detection of a common object.

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Index Terms

Computer Science
Information Sciences

Keywords

Face detection Facial landmark detection and recognition

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