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3D Face Recognition System for Windows

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Editors’ Review

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This Matlab-based system offers advanced 3D face recognition. It uses anatomical structure geometry to overcome limitations of 2D systems, providing illumination and viewpoint invariant identification.

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  • Pros

    • Provides 3D face recognition functionality within Matlab.
    • Utilizes anatomical face geometry for enhanced recognition.
    • Achieves illumination invariance via 3D surface data.
    • Offers viewpoint invariance through 3D model registration.
    • Supports integration of texture information for recognition.

  • Cons

    • Viewpoint invariance degree depends on 3D head model completeness.
    • Tested population limited to Caucasian individuals aged 18-40.
    • Validation database (GavabDB) does not include texture data.
    • Scalability or real-time performance information is not provided.
Icon of program: 3D Face Recognition Syste…

3D Face Recognition System for Windows

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Used 3D Face Recognition System for Windows?

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Full Specifications

GENERAL
Release
Latest update
Version
1.0
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows NT
  • Windows 2003
  • Windows XP
  • Windows 8
  • Windows 7
  • Windows 98
  • Windows 10
  • Windows Vista
  • Windows Server
  • Windows ME
  • Windows 2000
Additional Requirements
Matlab
POPULARITY
Total Downloads
2,019
Downloads Last Week
1
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Developer’s Description

By Luigi Rosa
Provide 3D face recognition system for Matlab.
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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