Key point detection method and device, electronic equipment and storage medium

Abstract

The invention relates to a key point detection method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining first feature maps of a plurality of scales for an input image,wherein the scales of the first feature map to be in a multiple relation; using a first pyramid neural network to perform forward processing on the first feature maps to obtain second feature maps in one-to-one correspondence with the first feature maps, wherein the second feature maps are the same as the first feature maps in one-to-one correspondence in scale; using a second pyramid neural network to perform reverse processing on the second feature maps to obtain third feature maps in one-to-one correspondence with the second feature maps, wherein the scales of the third feature maps are the same as those of the second feature maps in one-to-one correspondence with the third feature maps; and performing feature fusion processing on each third feature map, and obtaining the position of each key point in the input image by using the feature map after the feature fusion processing. The position of the key point can be accurately extracted.

Description

[0001] This application is a divisional application of a Chinese patent application submitted to the China Patent Office on November 16, 2018 with the application number 201811367869.4 and the application name "Key Point Detection Method and Device, Electronic Equipment and Storage Medium". technical field [0002] The present disclosure relates to the technical field of computer vision, and in particular to a key point detection method and device, electronic equipment and a storage medium. Background technique [0003] Human body key point detection is to detect the position information of key points such as joints or facial features from the human body image, so as to describe the posture of the human body through the position information of these key points. [0004] Because the human body is different in size in the image, the existing technology can usually use the neural network to obtain the multi-scale features of the image, which is used to finally predict the positi...

AI Technical Summary

Problems solved by technology

However, we found that using this method, it is not possible to fully mine and utilize multi-scale features, and the detection accuracy of key points is low.

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