Subtle expression recognition method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of biological recognition, and discloses a subtle expression recognition method. The method comprises the following steps of: performing optical flow processing on a to-be-detected facial expression video of a target person to obtain video processing data; performing spatial feature extraction on the video processing data to obtain a spatial vector set; performing time sequence feature extraction on the video processing data to obtain a time sequence vector set; carrying out fusion calculation on the space vector set and the time sequence vector set to obtain a space-time feature vector set; and performing subtle expression category analysis on the space-time feature vector set to obtain a subtle expression recognition result in the to-be-detected facial expression video. In addition, the invention also relates to a block chain technology, and the to-be-detected facial expression and the subtle expression recognition result thereof can be stored in a block chain. In addition, the invention also provides a subtle expression recognition device, electronic equipment and a storage medium. According to the subtle expression recognition method and device, the electronic equipment and the storage medium, the spatial features and the time sequence features of the subtle expression can be classified and analyzed at the same time, and the accuracy of subtle expression recognition is improved.

Description

technical field [0001] The invention relates to the field of biometric identification, in particular to a micro-expression recognition method, device, electronic equipment and computer-readable storage medium. Background technique [0002] Expressions are one of the important ways for humans to express emotions. In psychology, expressions are divided into macro expressions and micro expressions. Macro expressions are deceptive, but micro expressions can express the true emotions of human beings. Therefore, how to detect and identify the target person Micro-expressions are of great significance to fields such as human-computer interaction, interrogation, and lie detection. [0003] During the investigation and interrogation, micro-expression information such as facial muscle contraction texture and eyebrow floating of the suspect has been captured due to its short duration, low range of facial changes, and weak features. Through the local binary algorithm (LBP), the texture ...

AI Technical Summary

Problems solved by technology

However, the traditional LBP algorithm only analyzes and summarizes the spatial characteristics of the micro-expression in each frame of the image, and ignores the dynamic characteristics of the connection between frames in the video, because the micro-expression has the characteristics of short duration and low range of change. The micro-expression recognition method ignores short-term dynamic features, making the recognition rate still low

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