Micro expression recognition method based on optical flow and Fisher Vector coding

Abstract

The invention discloses a micro expression recognition method based on optical flow and Fisher Vector coding. The method comprises the following steps that: HOF (Histogram of Oriented Optical Flow) feature extraction is performed on a micro expression image sequence in a test sample, and first feature data X which are expressed by an equation described in the descriptions of the invention are obtained; Fisher Vector coding is performed on the first feature data X, so that second feature data F are obtained; and the second feature data F are identified based on a pre-trained classifier. According to the micro expression recognition method of the invention, the optical flow features are adopted to describe the micro movement of a micro expression; the optical flow features are coded through using Fisher Vector, so that desired information and variance information can be obtained; and therefore, the features of the micro expression can be expressed more fully, the influence of local noises can be reduced, and the robustness of the features of the micro expression can be improved, and the recognition rate of the micro expression can be improved.

Description

technical field [0001] The invention relates to the technical field of machine learning and pattern recognition, in particular to a micro-expression recognition method based on optical flow and FisherVector coding. Background technique [0002] The study of human facial expressions originated in the 19th century. Recently, foreign scholars Ekman and Erika conducted a study on facial mapping behavior, and verified that micro expressions can provide more comprehensive covert emotional information. Different from macro-expression, micro-expression is a kind of rapid expression with a short duration and low intensity. Although the duration is short, micro-expressions can better reveal the true emotions in people's hearts and provide a reliable basis for judging people's inner mental state. Therefore, they have important applications in the judicial system and clinical diagnosis. [0003] In foreign countries, the study of micro-expressions started earlier, not only proposing a...

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Problems solved by technology

[0004] However, the existing micro-expression recognition methods have problems such as poor robustness, easy to be disturbed by noise, and low recognition rate.

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