Supervised super-vector encoding for facial expression recognition
Pattern Recognition Letters(2014)
摘要
Expression recognition from faces with varying pose and illumination conditions is a challenging research area with growing interest. In this paper, we develop a novel supervised super-vector encoding framework to learn discriminative image feature representations. The framework is then validated on the Multi-PIE and BU3D-FE databases for multi-view facial expression recognition. Extensive experiments show that our supervised framework gives significant improvement over the unsupervised counterpart and outperforms the state-of-the-arts.
更多查看译文
关键词
face biometrics,facial expression recognition,gmm learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络