Facial Expression Recognition Using Directional Local Binary Pattern

Abstract:

Local binary pattern (LBP) descriptor could not efficiently describe the gray change in different directions of facial expressions characteristic regions. For this, the directional local binary pattern (DLBP) is put forward to represent facial geometrical characteristic. DLBP encodes the directional information of the face’s facial textures in horizontal, vertical and diagonal three directions, which can effectively describe the characteristic of facial muscles, wrinkles and other local deformation. Experimental results on JAFFE databases demonstrate the algorithm’s effectiveness, where nearly 5 percent recognition rate improvement is obtained beyond traditional LBP. Additional experiments verify robustness and reliability of the proposed DLBP operator within Gaussian white noise and pepper salt noise.

• Periodical: Applied Mechanics and Materials (Volumes 701-702)
• Pages: 395-399
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.701-702.395
• Online since: December 2014
• Authors: Ying Tong, Kun Wang, Liang Bao Jiao*
• Keywords: Central Nearest Neighbor Classification, DLBP, Facial Expression Recognition, Local Binary Pattern (LBP)

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