Thesis (MEng) -- Stellenbosch University , 1999. / ENGLISH ABSTRACT: In recent years face recognition has been a focus of intensive research but has still not
achieved its full potential, mainly due to the limited abilities of existing systems to cope
with varying pose and illumination. The most popular techniques to overcome this problem
are the use of 3-D models or stereo information as this provides a system with the necessary
information about the human face to ensure good recognition performance on faces with
largely varying poses.
In this thesis we present a novel approach to view-invariant face recognition that utilizes
stereo information extracted from calibrated stereo image pairs. The method is invariant
of scaling, rotation and variations in illumination. For each of the training image pairs a
number of facial feature points are located in both images using Gabor wavelets. From
this, along with the camera calibration information, a sparse 3-D mesh of the face can be
constructed. This mesh is then stored along with the Gabor wavelet coefficients at each
feature point, resulting in a model that contains both the geometric information of the
face as well as its texture, described by the wavelet coefficients. The recognition is then
conducted by filtering the test image pair with a Gabor filter bank, projecting the stored
models feature points onto the image pairs and comparing the Gabor coefficients from the
filtered image pairs with the ones stored in the model. The fit is optimised by rotating and
translating the 3-D mesh. With this method reliable recognition results were obtained on
a database with large variations in pose and illumination. / AFRIKAANSE OPSOMMING: Alhoewel gesigsherkenning die afgelope paar jaar intensief ondersoek is, het dit nog nie sy
volle potensiaal bereik nie. Dit kan hoofsaaklik toegeskryf word aan die feit dat huidige
stelsels nie aanpasbaar is om verskillende beligting en posisie van die onderwerp te hanteer
nie. Die bekendste tegniek om hiervoor te kompenseer is die gebruik van 3-D modelle of
stereo inligting. Dit stel die stelsel instaat om akkurate gesigsherkenning te doen op gesigte
met groot posisionele variansie.
Hierdie werk beskryf 'n nuwe metode om posisie-onafhanklike gesigsherkenning te doen
deur gebruik te maak van stereo beeldpare. Die metode is invariant vir skalering, rotasie
en veranderinge in beligting. 'n Aantal gesigspatrone word gevind in elke beeldpaar van die
oplei-data deur gebruik te maak van Gabor filters. Hierdie patrone en kamera kalibrasie
inligting word gebruik om 'n 3-D raamwerk van die gesig te konstrueer. Die gesigmodel wat
gebruik word om toetsbeelde te klassifiseer bestaan uit die gesigraamwerk en die Gabor
filter koeffisiente by elke patroonpunt.
Klassifisering van 'n toetsbeeldpaar word gedoen deur die toetsbeelde te filter met 'n Gabor
filterbank. Die gestoorde modelpatroonpunte word dan geprojekteer op die beeldpaar en
die Gabor koeffisiente van die gefilterde beelde word dan vergelyk met die koeffisiente wat
gestoor is in die model. Die passing word geoptimeer deur rotosie en translasie van die
3-D raamwerk. Die studie het getoon dat hierdie metode akkurate resultate verskaf vir 'n
databasis met 'n groot variansie in posisie en beligting.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/51090 |
| Date | 12 1900 |
| Creators | Eriksson, Anders |
| Contributors | Weber, D., Stellenbosch University. Faculty of Engineering. Dept. of Electrical & Electronic Engineering. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
| Format | 77 leaves : ill. |
| Rights | Stellenbosch University |
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