Micro-expression recognition method based on multi-scale spatial-temporal feature neural network

A neural network and spatio-temporal feature technology, applied in the field of image processing, can solve the problems of lack of abstract feature representation information, extraction of superficial information, etc.

Active Publication Date: 2021-03-26
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Claims
  • Application Information

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Problems solved by technology

The main disadvantage of these methods is to extract mostly superficial information from videos, lacking the information required for abstract feature representation

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  • Micro-expression recognition method based on multi-scale spatial-temporal feature neural network
  • Micro-expression recognition method based on multi-scale spatial-temporal feature neural network
  • Micro-expression recognition method based on multi-scale spatial-temporal feature neural network

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Embodiment Construction

[0044] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0045]figure 1 , the micro-expression recognition method based on the multi-scale spatio-temporal feature neural network provided by the embodiment of the present application, including:

[0046] S1: Obtain a micro-expression video set, and convert the micro-expression video set into a micro-expression image frame sequence sample set;

[0047] S2...

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Abstract

The invention relates to a micro-expression recognition method based on a multi-scale spatial-temporal feature neural network, and the method can learn the features of a spatial domain and a time domain of a micro-expression from a micro-expression video frame, and enables the features of the spatial domain and the time domain to be combined to form a more robust micro-expression feature. Meanwhile, aiming at the situation that the micro-expression occurs in the facial local area, the active local area generated by the micro-expression is combined with the global area to be used for micro-expression recognition. The problems that feature extraction between continuous frames of micro-expressions is insufficient, and the micro-expressions are relatively active in a local area are solved. Compared with other methods, the accuracy of spontaneous micro-expressions has certain advantages, and 78.7% of the accuracy fully shows that the method has good recognition effect on micro-expressions.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to a micro-expression recognition method based on a multi-scale spatio-temporal feature neural network. Background technique [0002] A micro-expression is a spontaneous expression that can neither be faked nor suppressed, produced when a person is trying to conceal inner emotions. When a person hides some real emotion in his heart, a micro-expression occurs, usually the duration of the micro-expression is 1 / 25-1 / 3 second. The small movement range and short duration of micro-expressions are a huge challenge to human naked eye recognition. Because micro-expressions cannot be forged and suppressed, they can be used as an important basis for judging people's subjective emotions. Through the development of facial micro-expression recognition technology, it is possible to effectively identify and interpret micro-expressions. Capturing the micro-expressions of people...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/049G06N3/08G06V40/174G06V40/161G06V40/168G06N3/045G06V40/176G06V10/82G06V10/774G06V10/454G06N3/084G06N3/044G06V40/172G06F18/2148
Inventor 陶建华张昊刘斌佘文祥
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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