Face recognition using scale-adaptive directional and textural features
作者：
Highlights：
• We propose a face descriptor based on a combination of directional and textural features.
• Discriminative and nearly illumination invariant directional features are introduced.
• Pyramid partitioning is used to capture local as well as holistic features.
• Experiments performed on six standard face datasets shows robustness of proposed descriptor.
• Algorithm achieves nearly perfect recognition rate on a number of standard face datasets.
摘要
•We propose a face descriptor based on a combination of directional and textural features.•Discriminative and nearly illumination invariant directional features are introduced.•Pyramid partitioning is used to capture local as well as holistic features.•Experiments performed on six standard face datasets shows robustness of proposed descriptor.•Algorithm achieves nearly perfect recognition rate on a number of standard face datasets.
论文关键词：Face classification,Face representation,Local Polynomial Approximation (LPA),Local Binary Patterns (LBP)
论文评审过程：Received 4 October 2012, Revised 9 October 2013, Accepted 13 November 2013, Available online 22 November 2013.
论文官网地址：https://doi.org/10.1016/j.patcog.2013.11.013
