Multiview active shape models with SIFT descriptors

This thesis presents techniques for locating landmarks in images of human faces. A modified Active Shape Model (ASM [21]) is introduced that uses a form of SIFT descriptors [68]. Multivariate Adaptive Regression Splines (MARS [40]) are used to efficiently match descriptors around landmarks. This modified ASM is fast and performs well on frontal faces. The model is then extended to also handle non-frontal faces. This is done by first estimating the face's pose, rotating the face upright, then applying one of three ASM submodels specialized for frontal, left, or right three-quarter views. The multiview model is shown to be effective on a variety of datasets.

Grantor dc:publisher.institution

Department of Electrical Engineering

Year dc:date.issued

2016

Author dc:creator

• Milborrow, Stephen

Advisor dc:contributor.advisor

• Nicolls, Fred C

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/22867

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/22867