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Skin based Occlusion Detection and Face Recognition using Machine Learning Techniques

by G. Suvarna Kumar, P.v.g.d. Prasad Reddy, M. Srinadh Swamy, Sumit Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 18
Year of Publication: 2012
Authors: G. Suvarna Kumar, P.v.g.d. Prasad Reddy, M. Srinadh Swamy, Sumit Gupta
10.5120/5640-7998

G. Suvarna Kumar, P.v.g.d. Prasad Reddy, M. Srinadh Swamy, Sumit Gupta . Skin based Occlusion Detection and Face Recognition using Machine Learning Techniques. International Journal of Computer Applications. 41, 18 ( March 2012), 11-15. DOI=10.5120/5640-7998

@article{ 10.5120/5640-7998,
author = { G. Suvarna Kumar, P.v.g.d. Prasad Reddy, M. Srinadh Swamy, Sumit Gupta },
title = { Skin based Occlusion Detection and Face Recognition using Machine Learning Techniques },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 18 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number18/5640-7998/ },
doi = { 10.5120/5640-7998 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:29:55.561976+05:30
%A G. Suvarna Kumar
%A P.v.g.d. Prasad Reddy
%A M. Srinadh Swamy
%A Sumit Gupta
%T Skin based Occlusion Detection and Face Recognition using Machine Learning Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 18
%P 11-15
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a detailed experimental study of occlusion detection in the controlled environmentsbased on skin color is proposed. The image is given as an input to the face detection algorithm to detect the faces. Some faces are not detected dueto occlusion, so an occlusion detection technique is implemented to detect all the occluded faces. Those occlusions are detected using skin color of the faces. This is implemented by using circular Hough transform through plotting of circles on the faces present in the image. In order to overcome the illumination problem, extraction of local SMQT features is done. After completion of face detection, occlusions are detected based on skin color and the respective spatial locations of the image are returned. To differentiate the skin colors with other colors, SVM classifier is used. Huge datasets are collected for the purpose of training. From the image database, the occluded faces are recognized by retrieving it through spatial location. This implementation is suitable for all face detection applications in constrained environments the experiment using this technique havegiven 94%accuracy.

References
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  2. C. Lawrence Zitnick, Takeo Kanade, "A Cooperative Algorithm for Stereo Matching and Occlusion Detection" CMU-RI-TR-99-35.
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  6. E. Osuna, R. Freund, and F. Girosi, "Training support vector machines:an application to face detection," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '97), 1997, pp. 193–199.
  7. Hongjun Jia and Aleix M. Martinez, "Support Vector Machines in Face Recognition with Occlusions", Computer Vision and Pattern Recognition - CVPR , pp. 136-141, 2009
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  9. Niranjan, M. "Support vector machines: a tutorial overview and critical appraisal" in Applied Statistical Pattern Recognition (Ref. No. 1999/063), IEE Colloquium on, 20 Apr 1999, ref number 1999/063.
Index Terms

Computer Science
Information Sciences

Keywords

Svm Classifier Smqt Features

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