Utilizing Viola Jones with Haar Cascade Along with Neural Networks for Face Detection and Recognition

Sarthak Arora; Karan Arora

Title:
Utilizing Viola Jones with Haar Cascade Along with Neural Networks for Face Detection and Recognition

Authors:
Karan Arora | Sarthak Arora

Cite This Article :

Karan Arora | Sarthak Arora "Utilizing Viola Jones with Haar Cascade Along with Neural Networks for Face Detection and Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1, December 2020, pp.284-291, URL: https://www.ijtsrd.com/papers/ijtsrd35848.pdf

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Abstract :
Viola–Jones object detection frameworkintroduced in 2001 by Dr. Paul Viola and Dr. Michael Jones is an object detection framework which can be trained for detecting a variety of object classes .It is primarily used for the problem of face detection.In most video recording or surveillance systems it became impossible for human beings to retrieve large image datasets and analyze them for potential results. Now-a-days accurate facial recognition has a great impact in our ecosystem be it face unlock or face recognition in cameras for auto adjust. Implemented in two stages our proposed methodology will first utilize one of the widely accepted methods to detect faces i.e. viola Jones which utilizes Haar Classifiers and in the second stage we will recognise the face using Principal Component Analysis (PCA) and Feed Forward Neural Network. Bio ID-Face-Database is used as a training database. Test is conducted on webcam video and image snapshots.

Keywords :
haar-features, Viola Jones, Image Analysis, face detection, feature extraction, face edge detection

Publication Details:

Unique Identification Number : IJTSRD35848

Published In : Volume-5 | Issue-1, December 2020

Page Number(s) : 284-291

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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