Abstract—Face recognition algorithms work properly only under strict conditions. There is no doubt that the system accuracy drops significantly when some of those conditions are not applied. In this paper, we take care of the most detrimental factor, variant head poses, to recognize the face. Novel method is proposed to construct the virtual view of face from a single frontal face. Instead of using the whole face, some patches are selected from only half of the face. Features are extracted via biorthogonal wavelet transform. Block of feed forward neural networks is applied to infer the mapping ratio between poses and gallery. CMU database is utilized to demonstrate the robustness of the proposed method.

Index Terms—Pose, biorthogonal wavelet transform, face recognito, human machine interaction.

The authors are with the Computer Vision, Video and Image Processing (CvviP) Research Lab, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia (e-mail:shahdi@fkegraduate.utm.my, syed@fke.utm.my)

Cite: Seyed Omid Shahdi and S. A. R. Abu-Bakar, "Face Recognition under Variant Head Poses Using Single Frontal Gallery Image and Facial Symmetry," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 288-292, 2012.