Automatic Detection of Face in Video Sequences by using Extended Semi Local Binary Patterns

Human Resources Management and Services

View Publication Info
 
 
Field Value
 
Title Automatic Detection of Face in Video Sequences by using Extended Semi Local Binary Patterns
 
Creator PANNEERSELVAM, ITHAYA RANI
T., Hari Prasath
 
Description Machine analysis of detection of the face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Extended Semi-Local Binary Patterns. For each frame, an aggregation of the pixel values over a neighborhood is considered and a local binary pattern is obtained. From these a binary code is obtained for each pixel and then histogram features is computed. Adaboost algorithm is used to learn and classify these discriminative features with the help of exemplar face and non-face signature of the images for detecting the location of face region in the frame. This Extended Semi Local Binary Pattern is sturdy to variations in illumination and noisy images. The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.
 
Publisher PiscoMed Publishing Pte Ltd
 
Date 2018-09-21
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://ojs.piscomed.com/index.php/HRMS/article/view/656
10.18282/hrms.v1i1.656
 
Source Human Resources Management and Services; Vol 1, No 1
 
Language eng
 
Relation http://ojs.piscomed.com/index.php/HRMS/article/view/656/615
 
Rights Copyright (c) 2018 Human Resources Management and Services
http://creativecommons.org/licenses/by-nc/4.0
 

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