Face detection and recognition using low quality video cameras

Face detection and recognition are applications of image processing and analysis. Though several system have already been implemented to detect and recognize faces from image sequences, there are still problems being faced like having to recognize through a real surveillance. This is mostly because...

Full description

Saved in:
Bibliographic Details
Main Authors: Blancas, Kevin T., Chan, Aleta Claribel T., Chua, Paul Vincent D., Yeung, Wing Ho S.
Format: text
Language:English
Published: Animo Repository 2008
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/14433
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_bachelors-15075
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-150752021-11-03T08:43:52Z Face detection and recognition using low quality video cameras Blancas, Kevin T. Chan, Aleta Claribel T. Chua, Paul Vincent D. Yeung, Wing Ho S. Face detection and recognition are applications of image processing and analysis. Though several system have already been implemented to detect and recognize faces from image sequences, there are still problems being faced like having to recognize through a real surveillance. This is mostly because of the poor quality of images and diminutive size of the faces. In this paper, the proponents present a simple and effective method to detect faces in low-quality video by using multi-module integration. The proponents combine skin detection module, template matching, and local face region analysis method into a single face detection system. In addition to that, a recognition module based on template matching using Pearson's Linear Correlation Coefficient is also discussed. Our results show that the combined face detection algorithm works fast and accurate in detecting faces with respect to the poor quality and sizes of faces." 2008-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/14433 Bachelor's Theses English Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
description Face detection and recognition are applications of image processing and analysis. Though several system have already been implemented to detect and recognize faces from image sequences, there are still problems being faced like having to recognize through a real surveillance. This is mostly because of the poor quality of images and diminutive size of the faces. In this paper, the proponents present a simple and effective method to detect faces in low-quality video by using multi-module integration. The proponents combine skin detection module, template matching, and local face region analysis method into a single face detection system. In addition to that, a recognition module based on template matching using Pearson's Linear Correlation Coefficient is also discussed. Our results show that the combined face detection algorithm works fast and accurate in detecting faces with respect to the poor quality and sizes of faces."
format text
author Blancas, Kevin T.
Chan, Aleta Claribel T.
Chua, Paul Vincent D.
Yeung, Wing Ho S.
spellingShingle Blancas, Kevin T.
Chan, Aleta Claribel T.
Chua, Paul Vincent D.
Yeung, Wing Ho S.
Face detection and recognition using low quality video cameras
author_facet Blancas, Kevin T.
Chan, Aleta Claribel T.
Chua, Paul Vincent D.
Yeung, Wing Ho S.
author_sort Blancas, Kevin T.
title Face detection and recognition using low quality video cameras
title_short Face detection and recognition using low quality video cameras
title_full Face detection and recognition using low quality video cameras
title_fullStr Face detection and recognition using low quality video cameras
title_full_unstemmed Face detection and recognition using low quality video cameras
title_sort face detection and recognition using low quality video cameras
publisher Animo Repository
publishDate 2008
url https://animorepository.dlsu.edu.ph/etd_bachelors/14433
_version_ 1718382513893670912