Method for recognizing happiness degree of crowd based on deep learning

A technology of deep learning and recognition methods, applied in the direction of neural learning methods, character and pattern recognition, acquisition/recognition of facial features, etc., can solve the problems of classification and recognition of few group expressions, few attentions, etc.

Active Publication Date: 2017-06-06
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

In view of the wider application value, people have more and more interest in understanding the performance of human emotional attributes, but from the perspective of emotional analysis, the scene changes in images are still little attention in the field of affective computing.
At present, in

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  • Method for recognizing happiness degree of crowd based on deep learning
  • Method for recognizing happiness degree of crowd based on deep learning
  • Method for recognizing happiness degree of crowd based on deep learning

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Embodiment Construction

[0054] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0055] like figure 2 As shown, the present invention discloses a method for identifying crowd happiness based on deep learning, which includes the following steps:

[0056] Step A), after classifying the single human face image manually marked according to the label and normalizing the image size, the database of the degree of happiness of the face and the database of the degree of occlusion of the face are obtained, and they are divided into a training set and a verification set respectively and carried out preprocessing operations;

[0057] Step B), respectively construct the convolutional neural network used to identify the degree of happiness of the face and the degree of occlusion of the face; the convolution and down-sampling process of the convolutional neural network is as follows figure 1 shown;

[0058] Step C), after setting the init...

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Abstract

The invention discloses a method for recognizing the happiness degree of a crowd based on deep learning. The method comprises: firstly classifying manually marked individual face images and normalizing image sizes to obtain a face happiness degree database and a face shielding degree database; separately dividing the face happiness degree database and the face shielding degree database into a training set and a verification set to train a convolution neural network; then identifying the happiness degree and the shielding degree of faces in an input group photo by using a trained network model; and finally calculating the happiness degree of the crowd in the image by using face happiness degree weighted way. The method analyzes the expression of the crowd in the image by using the deep learning, is more accurate compared with traditional methods of extracting PHOG and Gabor, and provides new ideas and approaches for crowd emotion recognition in the image.

Description

technical field [0001] The present invention relates to the field of image processing and pattern recognition, and relates to a crowd emotion recognition method, in particular to a crowd happiness recognition method based on deep learning. Background technique [0002] A lot of research on facial expression recognition can be seen in recent years, but few people pay attention to the emotions expressed by a group of people in the image. With the popularity of data sharing and the rise of social networking sites such as YouTube and Flickr, users upload hundreds of millions of social pictures and videos every day, such as parties, weddings, graduation banquets, etc. attended. Usually, these uploaded videos and images may contain one or more people, so learning about crowds is a critical step. [0003] For example, if it is necessary to guess the mood of people in a group photo of a group of people participating in a class reunion, it is still challenging to use the existing em...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/08
CPCG06N3/08G06V40/168G06V40/172G06V40/175G06F18/24G06F18/214
Inventor 张文静卢官明闫静杰李海波
Owner NANJING UNIV OF POSTS & TELECOMM
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