Multidimensional Bernstein polynomials and Bezier curves: Analysis of machine learning algorithm for facial expression recognition based on curvature

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摘要

In this paper, by using partial derivative formulas of generating functions for the multidimensional unification of the Bernstein basis functions and their functional equations, we derive derivative formulas and identities for these basis functions and their generating functions. We also give a conjecture and some open questions related to not only subdivision property of these basis functions, but also solutions of a higher-order special differential equations. Moreover, we provide an implementation for a real world problem of human facial expression recognition with the help of curvature of Bezier curves whose machine learning supported by statistical evaluations on feature vectors using in the aforementioned machine learning algorithm.

论文关键词:Facial expression recognition,Machine learning,Bezier curve,Generating function,Statistical evaluations,Bernstein basis function

论文评审过程:Received 16 July 2018, Revised 26 September 2018, Accepted 1 October 2018, Available online 25 October 2018, Version of Record 25 October 2018.

论文官网地址:https://doi.org/10.1016/j.amc.2018.10.012