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ICMCS
2005
IEEE

Using partial information for face recognition and pose estimation

10 years 4 months ago
Using partial information for face recognition and pose estimation
The main achievement of this work is the development of a new face recognition approach called Partial Principal Component Analysis (P2 CA), which exploits the novel concept of using only partial information for the recognition stage. This approach uses 3D data in the training stage but it permits to use either 2D or 3D data in the recognition stage, making the whole system more flexible. Preliminary experiments carried out on a multiview face database composed of 18 individuals have shown robustness against big pose variations obtaining higher recognition rates than the conventional PCA method. Moreover, the P2 CA method can estimate the pose of the face under different illuminations with accuracy of the 96.15% when classifying the face images in 0º, ±30º, ±45º, ±60º and ±90º views.
Antonio Rama, Francesc Tarres, Davide Onofrio, Ste
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICMCS
Authors Antonio Rama, Francesc Tarres, Davide Onofrio, Stefano Tubaro
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