This paper presents a new method to recognize posed and spontaneous expression through modeling their global spatial patterns in Restricted Boltzmann Machine (RBM). First, the displacements of facial feature points between apex and onset facial images are extracted as features, which capture spatial variations of facial points. Second, the point displacement related facial events are extracted from its displacements. Third, two RBM models are trained to capture spatial patterns embedded in posed and spontaneous expressions respectively. The recognition results on both USTC-NVIE and SPOS databases demonstrate the effectiveness of the proposed RBM approach in modeling complex spatial patterns embodied in posed and spontaneous expressions, and good performance on posed and spontaneous expression distinction.
CITATION STYLE
Wu, C., & Wang, S. (2016). Posed and spontaneous expression recognition through restricted boltzmann machine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9516, pp. 127–137). Springer Verlag. https://doi.org/10.1007/978-3-319-27671-7_11
Mendeley helps you to discover research relevant for your work.