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Expression recognition method and system

An expression recognition and expression technology, applied in neural learning methods, character and pattern recognition, image analysis, etc., can solve problems such as not focusing on pain points, and achieve the effect of enhancing feature discrimination and narrowing differences

Pending Publication Date: 2022-05-24
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0011] The method of the patent CN111353390A is to improve the structure of the neural network model, but the focus is on the overall expression recognition effect, and does not focus on the current pain points

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  • Expression recognition method and system

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Experimental program
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Embodiment 1

[0064] like figure 1 As shown, the facial expression recognition method of the present invention comprises the following steps:

[0065] Step 1: Use the camera to collect clear facial expression videos of many people, each person contains seven basic expressions. Extract frames from the collected video, extract frames with expressions in the video, and obtain valid face expression picture samples;

[0066] Step 2: Perform face detection and face key point detection on the face expression picture sample obtained in step 1. The specific method is to use the algorithm in the Dlib library, which can preliminarily obtain the face area and face key points. The transformation matrix method is used to align the face, so that the nose of all face images is in the middle of the picture;

[0067] Step 3: Label the categories to which the facial expression picture samples obtained in step 2 belong, and use 0-6 to represent seven expressions, respectively, to obtain a complete expression...

Embodiment 2

[0088] like figure 2 As shown, an expression recognition system includes:

[0089] The input module is used to input the facial expression image and the corresponding category label into the expression recognition system;

[0090] The expression acquisition module is used to process multiple input facial expression images, perform face detection and face alignment on the input image samples, and obtain the facial expression image samples;

[0091]a standardization processing module, used for standardizing the facial expression picture samples, so that the sizes of the facial expression pictures are the same, and the standardized facial expression picture samples are obtained;

[0092] The format conversion module is used to convert the obtained standardized facial expression pictures into the tensor format required by the neural network model;

[0093] Model management module for creating, managing and saving neural network models;

[0094] The feature extraction module is...

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Abstract

The invention discloses an expression recognition method and system, and belongs to the technical field of biological feature recognition. The method comprises the following steps: acquiring a facial expression picture sample and a corresponding category label; performing face detection and face alignment according to the face expression sample; establishing a deep neural network model, and sending the facial expression picture into the deep neural network model to extract features so as to obtain expression features; selecting a plurality of triads according to the expression category labels, wherein three samples included in each triad are from different categories; calculating a first loss value according to the expression features and the triple; calculating cross entropy loss as a second loss value according to the real category label and the obtained expression features; and sending the expression features into a classifier for classification, and outputting a classification result. The main purpose of the invention is to readjust the inter-class distance between negative expressions and improve the problem of poor negative expression recognition effect.

Description

technical field [0001] The invention belongs to the technical field of biological feature recognition, and in particular relates to an expression recognition method and system. Background technique [0002] Facial expression recognition is to analyze the input face picture to determine which type of expression the current input face picture belongs to. Common expression recognition methods usually classify seven basic expressions, including: happy, surprised, neutral, fearful, disgusted, angry, and sad. [0003] Most of the existing expression recognition methods use deep learning convolutional neural networks to extract facial expression features and classify them. The obvious flaw shared by current methods is that the accuracy of negative expressions is significantly lower than that of positive expressions. The so-called positive expressions are expressions with positive emotions, including happiness and surprise, and negative expressions are expressions with negative em...

Claims

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Application Information

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IPC IPC(8): G06V40/16G06N3/08G06K9/62G06V10/82G06V10/774
CPCG06N3/08G06T2207/20081G06T2207/20084G06F18/214
Inventor 米建勋张美欣
Owner CHONGQING UNIV OF POSTS & TELECOMM