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Home / Graduate / M.S. Theses Completed
  Neşe Alyüz, 2008  [download thesis]    

Thesis Title

3D Face Registration Using Multiple Average Models


Three dimensional (3D) face recognition is a frequently used
biometric method and its performance is substantially dependent on
the accuracy of registration. In this work, we explore registration
techniques. Registration aligns two faces and make a comparison
possible between the two surfaces. In the literature, best results
have been achieved by a one-to-all approach, where a test face is
aligned to each gallery face separately. Unfortunately, the
computational cost of this approach is high. To overcome the
computational bottleneck, we examine registration based on an
Average Face Model (AFM). We propose a better method for the
construction of an AFM. To improve the registration, we propose to
group faces and register with category-specific AFMs. We compare the
groups formed by clustering in the face space with the groups based
on morphology and gender. We see that gender and morphology classes
exist, when faces are categorized with the clustering approach. As a
result of registering via an AFM, it is possible to apply regular
re-sampling on the depth values. With regular re-sampling,
improvements in recognition performance and comparison time were
obtained. As another factor causing diversity in the face space, we
explore expression variations. To reduce the negative effect of
expression in registration and recognition, we propose a
region-based registration method. We divide the facial surface into
several logical segments, and for each segment we create an Average
Region Model (ARM). Registering via each ARM separately, we examine
regional recognition performance. We see that even though some
regions such as nose or eye area are less affected by expression
variations, no single region is sufficient by itself and the use of
all regions is beneficial in recognition. We experiment with several
fusion techniques to combine results from individual regions and
obtain performance increase.
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