Evaluation of 3D face recognition using registration and PCA

Theodoros Papatheodorou, Daniel Rueckert

Research output: Contribution to journalConference articlepeer-review

31 Scopus citations


We introduce a novel technique for face recognition by using 3D face data that has been reconstructed from a stereo camera system. The face data consists of a dense 3D mesh of vertices describing the facial shape and geometry as well as a 2D texture map describing the facial appearance of each subject. We propose a recognition algorithm based on two steps: The first step involves the cleaning of the facial surface followed by a registration and normalization to a standard template face. The second step involves the creation of a PCA model and the use of a reduced dimensionality face space for the calculation of facial similarity. We use this technique on 3D surface and texture data comprising 83 subjects. Our results demonstrate the wealth of 3D information on the face as well as the importance of standardization and noise elimination in the datasets.

Original languageEnglish
Pages (from-to)997-1009
Number of pages13
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
StatePublished - 2005
Externally publishedYes
Event5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005 - Hilton Rye Town, NY, United States
Duration: 20 Jul 200522 Jul 2005


Dive into the research topics of 'Evaluation of 3D face recognition using registration and PCA'. Together they form a unique fingerprint.

Cite this