Glasses removing method and device and communication equipment

Abstract

The invention provides a glasses removing method and device and communication equipment. The method comprises the following steps: segmenting an initial face image into a first image block, a second image block and a third image block; performing up-sampling operation and down-sampling operation on the second image block in sequence through the glasses removal shallow convolutional neural network, and reconstructing the image through convolution and pooling to obtain a reconstructed glasses-free image block consistent with the second image block in size; splicing the reconstructed glasses-free image block, the first image block and the third image block to obtain a complete glasses-free face image; according to the embodiment of the invention, the feature map with higher resolution is obtained through up-sampling, and the quality of the reconstructed image is improved; then feature extraction and reconstruction are carried out on the feature map through pooling, a double-branch convolution module and other operations, the process is a down-sampling process at the same time, and the size of the processed feature map is reduced to the size of an original map; the number of layers of the neural network is small, and therefore small calculation amount and high forward operation efficiency are kept.

Description

technical field [0001] The present invention relates to the field of communication technologies, and in particular, to a method, device and communication equipment for removing glasses. Background technique [0002] As one of the most common occluders in face images, glasses will interfere with the extraction of face features, resulting in a decrease in the accuracy of face recognition. According to the different technologies used, the existing face image glasses removal methods can be roughly divided into two categories: traditional methods based on Principal Component Analysis (PCA) and methods based on Convolution Neural Networks (CNN). . Among them, the PCA-based glasses removal method was proposed earlier. The principle is to find the most important components in the data through principal component analysis, remove the redundancy and noise in the high-dimensional vector space, and use these principal components to represent the original data. Based on the face image ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the embodiment of the present invention is to provide a glasses removal method, device and communication equipment to solve the problem of low image quality output by the glasses removal deep convolutional neural network model in the prior art, a large amount of network calculation, and forward-running problems. longer question

Images