2005 | OriginalPaper | Chapter
Selection and Extraction of Patch Descriptors for 3D Face Recognition
Authors : Berk Gökberk, Lale Akarun
Published in: Computer and Information Sciences - ISCIS 2005
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In 3D face recognition systems, 3D facial shape information plays an important role. 3D face recognizers usually depend on
point cloud representation
of faces where faces are represented as a set of 3D point coordinates. In many of the previous studies, faces are represented holistically and the discriminative contribution of local regions are assumed to be equivalent. In this work, we aim to design a local region-based 3D face representation scheme where the discriminative contribution of local facial regions are taken into account by using a subset selection mechanism. In addition to the subset selection methodology, we have extracted patch descriptors and coded them using Linear Discriminant Analysis (LDA). Our experiments on the
3D_RMA
database show that both the proposed floating backward subset selection scheme and the LDA-based coding of region descriptors improve the classification accuracy, and reduce the representation complexity significantly.