Thesiszxc
School of Computer Science and Information Technology
University of Nottingham
Orthoface for Recognition
and
Pose-Invariant Face Recognition
Voon Piao SIANG
2001
A thesis in partial fulfilment of the requirement of University of Nottingham for the degree of Master of Philosophy
This copy of thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that no information derived from it may be published without the author’s prior written consent. Abstract
This research project focuses primarily on the development of orthoface for recognition. The orthoface method is a novel face recognition algorithm. Orthoface method transforms faces from image space to face space. It achieves a dimension reduction similar to that of eigenface. All of the classification methods applicable to eigenface method can be applied to the orthoface method without any further modification. It maximises the inter-class scattering, and minimizes the intra-class scattering, which has been the weakness of the conventional eigenface method.
The project matrix of the training face from the orthoface method forms an upper-triangular matrix. Each training face has a different number of coefficients allowing better discrimination and classification. A new classification technique is applied, in addition to the supports for the traditional classifiers. The new classification technique does not require comparison between test face coefficients and training face coefficients. This improves recognition speed significantly. It is estimated conservatively that such an improvement is no less than 10 times faster.
Using the basic orthoface method, the recognition rate is 87%. By increasing to 3 training faces per subject, the recognition rate improves to 92%. However, using hand-picked difficult test faces, a recognition rate of 83% is
University of Nottingham
Orthoface for Recognition
and
Pose-Invariant Face Recognition
Voon Piao SIANG
2001
A thesis in partial fulfilment of the requirement of University of Nottingham for the degree of Master of Philosophy
This copy of thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that no information derived from it may be published without the author’s prior written consent. Abstract
This research project focuses primarily on the development of orthoface for recognition. The orthoface method is a novel face recognition algorithm. Orthoface method transforms faces from image space to face space. It achieves a dimension reduction similar to that of eigenface. All of the classification methods applicable to eigenface method can be applied to the orthoface method without any further modification. It maximises the inter-class scattering, and minimizes the intra-class scattering, which has been the weakness of the conventional eigenface method.
The project matrix of the training face from the orthoface method forms an upper-triangular matrix. Each training face has a different number of coefficients allowing better discrimination and classification. A new classification technique is applied, in addition to the supports for the traditional classifiers. The new classification technique does not require comparison between test face coefficients and training face coefficients. This improves recognition speed significantly. It is estimated conservatively that such an improvement is no less than 10 times faster.
Using the basic orthoface method, the recognition rate is 87%. By increasing to 3 training faces per subject, the recognition rate improves to 92%. However, using hand-picked difficult test faces, a recognition rate of 83% is