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Published on: December 3, 2013
Three-dimensional face recognition using shapes of facial curves
Chafik Samir1, Anuj Srivastava, Mohamed Daoudi
1LIFL (UMR/USTL CNRS 8022), Cite Scientifique, Villeneuve d'Ascq, France. chafik@enic.fr
IEEE Transactions on Pattern Analysis and Machine Intelligence
|October 27, 2006
Summary
This study introduces a novel method for 3D face recognition using facial curves derived from depth functions. Comparing these curves via geodesic lengths on a shape manifold achieves high recognition accuracy.
Area of Science:
- Computer Vision
- Biometrics
- Geometric Deep Learning
Background:
- 3D face recognition is crucial for security and identification.
- Existing methods often struggle with variations in pose and expression.
- Representing facial surfaces effectively remains a challenge.
Purpose of the Study:
- To develop a robust 3D face recognition system.
- To utilize facial curves as discriminative shape descriptors.
- To compare surface shapes implicitly through their curve representations.
Main Methods:
- Facial surfaces are represented by unions of level curves (facial curves) of the depth function.
- Surface shape comparison is performed implicitly using the shapes of these facial curves.
- A differential geometric approach computes geodesic lengths between closed curves on a shape manifold.
Main Results:
- The proposed method demonstrates good recognition performance on two 3D face databases.
- Nearest-neighbor classification using facial curve comparisons proved effective.
- The approach successfully captures and compares intricate facial surface geometries.
Conclusions:
- Facial curves offer a powerful representation for 3D face recognition.
- Implicit shape comparison using geodesic distances is a viable strategy.
- This method shows promise for enhancing the accuracy and robustness of biometric systems.
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