Frontal Facial Pose Recognition Using a Discriminant Splitting Feature Extraction Procedure
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| Title | Frontal Facial Pose Recognition Using a Discriminant Splitting Feature Extraction Procedure |
| Authors | |
| Abstract | Frontal facial pose recognition deals with classifying facial images into two-classes: frontal and non-frontal. Recognition of frontal poses is required as a preprocessing step to face analysis algorithms (e.g. face or facial expression recognition) that can operate only on frontal views. A novel frontal facial pose recognition technique that is based on discriminant image splitting for feature extraction is presented in this paper. Spatially homogeneous and discriminant regions for each facial class are produced. The classical image splitting technique is used in order to determine those regions. Thus, each facial class is characterized by a unique region pattern which consists of homogeneous and discriminant 2-D regions. The mean intensities of these regions are used as features for the classification task. The proposed method has been tested on data from the XM2VTS facial database with very satisfactory results. |
| Publisher | University of Zagreb, University Computing Centre - SRCE |
| Date | 2012-02-09 |
| Source | Journal of Computing and Information Technology Vol 19, No 4 (2011): Special Issue: Selected Papers from ITI 2011 Conference |
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