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Human target recognition has been an active research area
in the last years, with a major emphasis on automatic
detection and matching of faces in still images and videos, for
the purposes of verification and identification. Performance
of 2D face matching systems depends on their capability of
being insensitive to critical factors such as facial expressions,
makeup and aging, but mainly hinges upon extrinsic factors
such as illumination differences, camera viewpoint and scene
geometry. However, the inherent limitations of 2D face matching have
supported the belief that effective recognition of identity should
be obtained through multi-biometric technologies. In particular,
the exploitation of the geometry of the anatomical structure of
the face rather than its appearance, with definition of algorithms
and systems for 3D face matching has been a growing field
of research in the very recent years. 3D Face recognition systems aim to use the additional 3D data to eliminate some of the
intrinsic problems associated with 2D recognition systems. For example, the 3D surface of a
face is invariant to changes in lighting conditions and hence recognition systems that use this
data should be, by definition, illumination invariant. Furthermore, given that it is possible to
register a number of 3D models to a base pose, such a system would also be viewpoint
invariant (although to what degree depends on the completeness of the 3D head model). In
addition to the 3D data it remains possible to capture texture information and thus use all the
available data to guide the recognition process.
Code has been tested on GavabDB Database. GavabDB is a 3D face database.
It contains 549 three-dimensional images of facial surfaces. These meshes correspond to 61 different individuals
(45 male and 16 female) having 9 images for each person. The total of the individuals are Caucasian and their age is
between 18 and 40 years old. Each image is given by a mesh of connected 3D points of the facial surface without texture.
The database provides systematic variations with respect to the pose and the facial expression.
Index Terms: Matlab, source, code, 3D, face, recognition, verification, model, matching, virtual, reality, modeling, language, vrml.
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Figure 1. 3D face model |
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A simple and effective source code for 3D Face Recognition System. |
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Demo code (protected
P-files) available for performance evaluation. Matlab Image Processing Toolbox is required.
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Release |
Date |
Major features |
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1.0 |
2012.06.11 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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3D Face Recognition System. Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 44 EUROS (less
than 62 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of 3D Face Recognition System. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 14 SP1. Matlab Image Processing Toolbox is required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
