کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
534279 | 870241 | 2014 | 7 صفحه PDF | دانلود رایگان |
• A novel supervised super-vector encoding framework to learn discriminative image features.
• The framework is validated for multiview facial expression recognition.
• The supervised framework gives significant improvements and outperforms the state-of-the-arts.
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.
Journal: Pattern Recognition Letters - Volume 46, 1 September 2014, Pages 89–95