Publication:
3D face recognition by projection based methods

Thumbnail Image

Departments

School / College / Institute

Program

KU-Authors

KU Authors

Co-Authors

Dutaǧaci, Helin
Sankur, Bülent

Publication Date

Language

Embargo Status

NO

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

In this paper, we investigate recognition performances of various projection-based features applied on registered 3D scans of faces. Some features are data driven, such as ICA-based features or NNMF-based features. Other features are obtained using DFT or DCT-based schemes. We apply the feature extraction techniques to three different representations of registered faces, namely, 3D point clouds, 2D depth images and 3D voxel. We consider both global and local features. Global features are extracted from the whole face data, whereas local features are computed over the blocks partitioned from 2D depth images. The block-based local features are fused both at feature level and at decision level. The resulting feature vectors are matched using Linear Discriminant Analysis. Experiments using different combinations of representation types and feature vectors are conducted on the 3D-RMA dataset.

Source

Publisher

Society of Photo-optical Instrumentation Engineers (SPIE)

Subject

Computer science, Data reduction, Discrete Fourier transforms

Citation

Has Part

Source

Proceedings of SPIE

Book Series Title

Edition

DOI

10.1117/12.643089

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

1

Views

1

Downloads

View PlumX Details