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Facial Expression Recognition Method Based on Parallel Convolutional Neural Network Feature Map Fusion

A convolutional neural network and facial expression recognition technology, applied in the field of image recognition, can solve the problem of unsatisfactory recognition effect of small expression features, and achieve the effect of increasing feature expression ability and facilitating training.

Active Publication Date: 2022-02-11
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

The conventional CNN, DBN, and RNN models have a certain recognition effect on expressions with large differences, but the recognition effect on small expression features is not ideal.

Method used

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  • Facial Expression Recognition Method Based on Parallel Convolutional Neural Network Feature Map Fusion
  • Facial Expression Recognition Method Based on Parallel Convolutional Neural Network Feature Map Fusion
  • Facial Expression Recognition Method Based on Parallel Convolutional Neural Network Feature Map Fusion

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Embodiment Construction

[0043] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0044] The technical scheme that the present invention solves the problems of the technologies described above is:

[0045] The feature fusion facial expression recognition method of a kind of parallel convolutional neural network provided by the present embodiment comprises the following steps:

[0046] (1) The acquired facial expression image is preprocessed by intercepting the face area and numerical normalization:

[0047] Capture face area: Get the face area and select an image area with a size of 256×256 for interception.

[0048] Normalization: Normalize the acquired image so that the image value is in the range of [0,1]. Divide the image numerical matrix by 255 to obtain the image matrix informa...

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Abstract

The present invention claims a method for recognizing facial expressions based on the fusion of parallel convolutional neural network feature maps. This method simulates the human binocular visual channel, designs a convolutional neural network with a parallel structure, and fuses the feature maps of the parallel channels after the convolutional pooling layer; Connection output, the other channel uses dense full connection output, and the last two outputs are fused and classified; using facial expression data for model training to achieve a high recognition rate, use test samples to test the recognition effect of the model, and obtain high recognition accuracy The rate provides a new method for emotion analysis and facial expression recognition.

Description

technical field [0001] The invention belongs to the field of image recognition, in particular to a method for extracting and recognizing facial expression features by using a parallel convolutional neural network. Background technique [0002] Facial expressions contain rich emotional real information, and accurate and efficient recognition of facial expressions is an important research direction in the field of image vision. Facial expression information can be used in many fields such as distance education, auxiliary medical treatment, criminal detection and lie detection. Facial expression recognition technology is a process of classifying and identifying feature information after extracting facial expression features through a specific method. [0003] At present, the commonly used feature extraction methods for facial expression recognition can be divided into methods based on shape models and texture models. Among them, the active appearance model is mainly based on ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/16G06V30/19G06N3/04
CPCG06V40/174G06N3/045G06F18/2411G06F18/253
Inventor 蔡军昌泉蔡芳唐贤伦陈晓雷魏畅伍亚明林文星
Owner CHONGQING UNIV OF POSTS & TELECOMM
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