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An automated tool for face recognition using visual attention and active shape models analysis.

A Faro¹, D Giordano, C Spampinato

¹Dipt. di Ingegneria Informatica e Telecomun., Catania Univ., Italy. afaro@diit.unict.it

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|October 20, 2007

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This study introduces an automated facial recognition system that uses computational attention to identify key facial features. This approach enhances face modeling and recognition accuracy for improved performance.

Area of Science:

Computer Science
Biometrics
Image Processing

Background:

Automated facial recognition is crucial for security and identification.
Accurate identification of facial features is essential for robust facial recognition systems.

Purpose of the Study:

To present an automated approach for facial recognition using computational attention.
To leverage Focus of Attention (FOA) for identifying salient facial features.

Main Methods:

Utilized a computational attention module to automatically detect relevant facial features.
Employed the active contour model (ACM) for feature landmarking.
Adopted the active shape model (ASM) for flexible facial feature modeling.

Main Results:

Related Experiment Videos

The system successfully identifies key facial features for learning and recognition.
The integration of ACM and ASM provides a flexible and accurate facial model.

Conclusions:

The proposed automated approach offers an effective method for facial recognition.
Further improvements can be explored to enhance system performance and applicability.