Micro-expression recognition method based on difference slice energy diagram and Gabor transformation

Abstract

The invention provides a micro-expression recognition method based on a difference slice energy diagram and Gabor transformation. The micro-expression recognition method comprises the following steps: constructing a micro-expression sequence difference slice energy diagram, calculating micro-expression frames containing change regions in a micro-expression periodic sequence, graying the micro-expression sequence to extract micro-expression difference slices, and overlapping micro-expression difference slice frame sequences to obtain a micro-expression difference energy diagram; extracting the characteristics of the difference slice energy diagram, constructing a Gabor filter kernel function, performing Gabor characteristic extraction on the difference slice energy diagram, sampling the extracted characteristics, writing the characteristics of each sample in a column vector form, maximizing the quotient of inter-class divergence and intra-class divergence through linear discriminant analysis with supervisory information, and further extracting the characteristics of each sample; performing classification and identification, training a model according to training data, and predicting and classifying test samples according to the model. The method provided by the invention has general applicability. Compared with an existing method, the method provided by the invention has a higher identification rate.

Description

technical field [0001] The invention relates to a micro-expression recognition method based on differential slice energy graph and Gabor transformation, and belongs to the technical field of machine learning and pattern recognition in computer applications. technical background [0002] Micro-expression is a fast, imperceptible facial expression that people show when they are trying to suppress and hide their true emotions. Its duration is generally only 1 / 25 to 1 / 5 second. Some researchers also refer to micro-expression as The duration is defined as less than 1 / 2s, which is often ignored by people. However, Ekman et al.'s research on facial mapping behaviors confirmed that micro-expressions can more fully expose people's hidden emotions, and it can better express people's true emotions. In recent years, during the development of psychological diagnosis and the construction of national defense and security, micro-expressions, as a means of detecting lies and violent tendenc...

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Problems solved by technology

However, this method has high requirements on the performance of computer hardware equipment, it is difficult to determine the

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