Pet image emotion recognition method based on deep residual network

Abstract

The invention provides a pet image emotion recognition method based on a deep residual network, and the method comprises the steps: obtaining the audio and video of a single pet under different emotions, carrying out the preprocessing according to the audio, and extracting the sound features; performing statistical classification and emotion marking on the audio according to the sound features, and extracting a corresponding single-frame picture according to a time sequence and the video to obtain a pet image emotion data set with emotion marks; constructing a pet emotion classification algorithm model, and taking the pet image emotion data set as training data to perform model training; and performing target detection and emotion deduction on the pet through the trained model. According to the method, the determinacy of pet emotion recognition can be improved, and the inference speed and precision of recognition are improved.

Description

technical field [0001] The invention relates to the technical field of emotion recognition, in particular to a pet image emotion recognition method based on a deep residual network. Background technique [0002] At present, there are more and more pets in the family, and the communication between people and pets is also increasing. However, people often cannot effectively recognize the emotions expressed by pets, causing communication barriers, causing pets to be out of control, and pets to bite passers-by. Case. Experienced pet owners can accurately judge the pet's emotions through the tone, volume, frequency, etc. of the pet's voice, so as to provide effective comfort methods, but this ability is not possessed by every pet owner. [0003] Existing recognition methods based on audio data mainly use cepstral coefficient formants and zero-crossing rates as characteristic parameters to establish statistical models such as Gaussian mixture models, or use unsupervised clusterin...

AI Technical Summary

Problems solved by technology

[0004] The invention provides a pet image emotion recognition method based on a deep residual network, which solves the problem of inaccurate recognition existing in pet emotion recognition based on audio data, improves the certainty of pet emotion recognition, and improves the inference speed and accuracy of recognition

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