Head pose estimation based on nonlinear interpolative mapping

The performance of face recognition systems depends on conditions being consistent, including lighting, pose and facial expression. To solve the problem produced by pose variation it is suggested to pre-estimate the pose orientation of the given head image before it is recognized. In this paper, we...

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Bibliographic Details
Main Authors: Hwei-Jen Lin, Chen-Wei Chang, I-Chun Pai
Format: Conference Proceeding
Language:English
Subjects:
Access control
Face detection
Face recognition
Fingerprint recognition
head pose estimation
Image recognition
Isomap
Linear discriminant analysis
Magnetic heads
nonlinear interpolative mapping
Radial Basis Function (RBF)
Security
Support vector machines
Surveillance
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Summary:The performance of face recognition systems depends on conditions being consistent, including lighting, pose and facial expression. To solve the problem produced by pose variation it is suggested to pre-estimate the pose orientation of the given head image before it is recognized. In this paper, we propose a head pose estimation method that is an improvement on the one proposed by N. Hu et al. The proposed method trains in a supervised manner a nonlinear interpolative mapping function that maps input images to predicted pose angles. This mapping function is a linear combination of some Radial Basis Functions (RBF). The experimental results show that our proposed method has a better performance than the method proposed by Nan Hu et al. in terms of both time efficiency and estimation accuracy.
DOI:10.1109/JCPC.2009.5420207