Abstract
One of the most challenging factors in face recognition is pose variation. This paper proposes an appropriate framework to identify images across pose. The input profile image is classified to a pose range. After that, this image is matched with the same pose range images from a certain database to determine its identification. In this framework, descriptors which are based on Local Binary Patterns are used to extract features of all images. Experiments on the FERET database prove the robustness of the proposed framework based on comparison with other approaches.
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Nguyen, NQ.H., Le, T.H. (2015). Pose Estimation Using Local Binary Patterns for Face Recognition. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Perspectives and Applications. Advances in Intelligent Systems and Computing, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-319-18476-0_5
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DOI: https://doi.org/10.1007/978-3-319-18476-0_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18475-3
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