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Face recognition using Hidden Markov Models

This thesis relates to the design, implementation and evaluation of statistical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on is...

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Main Author: Ballot, Johan Stephen Simeon
Other Authors: Du Preez, J. A.
Format: Thesis
Language:English
Published: Stellenbosch : University of Stellenbosch 2008
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access_status_str Open Access
author Ballot, Johan Stephen Simeon
author2 Du Preez, J. A.
author_browse Ballot, Johan Stephen Simeon
Du Preez, J. A.
author_facet Du Preez, J. A.
Ballot, Johan Stephen Simeon
author_sort Ballot, Johan Stephen Simeon
collection Thesis
dc_rights_str_mv University of Stellenbosch
description This thesis relates to the design, implementation and evaluation of statistical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on issues like background noise, lighting and position of key features (ie. the eyes, lips etc.). Using an approach which specifically uses an embedded Hidden Markov Model along with spectral domain feature extraction techniques, shows that these dependencies may be lessened while high recognition rates are maintained.
format Thesis
id oai:scholar.sun.ac.za:10019.1/2577
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:42:38.497Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2008
publishDateRange 2008
publishDateSort 2008
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/2577 Face recognition using Hidden Markov Models Ballot, Johan Stephen Simeon Du Preez, J. A. Herbst, B. M. University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Theses -- Electrical and electronic engineering Dissertations -- Electrical and electronic engineering Human face recognition (Computer science) Pattern recognition systems Markov processes Electrical and Electronic Engineering This thesis relates to the design, implementation and evaluation of statistical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on issues like background noise, lighting and position of key features (ie. the eyes, lips etc.). Using an approach which specifically uses an embedded Hidden Markov Model along with spectral domain feature extraction techniques, shows that these dependencies may be lessened while high recognition rates are maintained. 2008-06-30T10:39:25Z 2010-06-01T08:52:45Z 2008-06-30T10:39:25Z 2010-06-01T08:52:45Z 2005-03 Thesis http://hdl.handle.net/10019.1/2577 en University of Stellenbosch application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Theses -- Electrical and electronic engineering
Dissertations -- Electrical and electronic engineering
Human face recognition (Computer science)
Pattern recognition systems
Markov processes
Electrical and Electronic Engineering
Ballot, Johan Stephen Simeon
Face recognition using Hidden Markov Models
title Face recognition using Hidden Markov Models
title_full Face recognition using Hidden Markov Models
title_fullStr Face recognition using Hidden Markov Models
title_full_unstemmed Face recognition using Hidden Markov Models
title_short Face recognition using Hidden Markov Models
title_sort face recognition using hidden markov models
topic Theses -- Electrical and electronic engineering
Dissertations -- Electrical and electronic engineering
Human face recognition (Computer science)
Pattern recognition systems
Markov processes
Electrical and Electronic Engineering
url http://hdl.handle.net/10019.1/2577
work_keys_str_mv AT ballotjohanstephensimeon facerecognitionusinghiddenmarkovmodels