Pose-robust face recognition with Huffman-LBP enhanced by Divide-and-Rule strategy
作者：
Highlights：
• A novel LBP-like feature is proposed which takes the contribution of contrast value into consideration by Huffman coding.
• The Divide-and-Rule strategy is applied to both face representation and classification with the goal of improving the robustness to pose variation.
• Face representation via Region Selection Factor (RSF) is suggested in our method to treat the face images of different poses specifically rather than generally.
• In order to further make the method tolerate the rotations, we perform the face classification at the patch-level using a patchbased SRC fusion classification strategy.
摘要
•A novel LBP-like feature is proposed which takes the contribution of contrast value into consideration by Huffman coding.•The Divide-and-Rule strategy is applied to both face representation and classification with the goal of improving the robustness to pose variation.•Face representation via Region Selection Factor (RSF) is suggested in our method to treat the face images of different poses specifically rather than generally.•In order to further make the method tolerate the rotations, we perform the face classification at the patch-level using a patchbased SRC fusion classification strategy.
论文关键词：Face recognition across pose,LBP,Huffman,Divide-and-Rule strategy
论文评审过程：Received 6 May 2017, Revised 22 October 2017, Accepted 7 January 2018, Available online 10 January 2018, Version of Record 20 January 2018.
论文官网地址：https://doi.org/10.1016/j.patcog.2018.01.003
