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A dynamic framework based on local Zernike moment and motion history image for facial expression recognition
2017
Pattern Recognition
A dynamic descriptor facilitates robust recognition of facial expressions in video sequences. The current two main approaches to the recognition are basic emotion recognition and recognition based on facial action coding system (FACS) action units. In this paper we focus on basic emotion recognition and propose a spatiotemporal feature based on local Zernike moment in the spatial domain using motion change frequency. We also design a dynamic feature comprising motion history image and entropy.
doi:10.1016/j.patcog.2016.12.002
fatcat:btjkw62p3nferkj2xqdb4vatpu