Human body key point identification method and device, intelligent terminal and storage medium
A recognition method and key point location technology, applied in the field of deep neural network, can solve the problems of large amount of calculation, long prediction time, large amount of parameters of deep neural network model, etc., and achieve the effect of reducing the amount of parameters and shortening the prediction time.
Pending Publication Date: 2021-04-27
KONKA GROUP +3
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[0005] The main purpose of the present invention is to provide a human body key point recognition method, device, intelligent terminal and storage medium, aiming to solve the problems of deep neural network model represented by HRNet model in the prior art with large parameters, large amount of calculation, and prediction consumption. It takes a long time and is not conducive to porting to embedded platforms such as mobile terminals for use
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[0054]In the following description, specific details such as specific system structures, techniques such as specific system structures, such as specific system structures are presented in order to illustrate, in order to thorns the embodiments of the present invention. However, those skilled in the art will appreciate that the present invention may be implemented in other embodiments without these specific details. In other cases, a detailed description of well known systems, devices, circuits, and methods is omitted to avoid unnecessary details to prevent the description of the present invention.
[0055]It should be understood that when used in the present specification and the appended claims, the term "includes" indicating the presence of the described features, overall, steps, operations, elements, and / or components, but does not exclude one or more other features. , Overall, steps, operation, presence or addition of elements, components, and / or sets thereof.
[0056]It should al...
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The invention discloses a human body key point recognition method and device, an intelligent terminal and a storage medium, and the method comprises the steps: obtaining a to-be-detected human body image; obtaining a compressed high-resolution feature network model; detecting the to-be-detected human body image based on the compressed high-resolution feature network model to obtain human body key point position information in the to-be-detected human body image; and outputting the human body key point position information. According to the human body key point recognition method, the existing high-resolution feature network model is compressed, and the human body key point position information is detected and obtained based on the compressed high-resolution feature network model, so that compared with the prior art, the parameter amount and the calculation amount are reduced, the prediction time is shortened, and the prediction efficiency is improved. The model can be transplanted to a mobile terminal and other embedded platforms for use.
Description
Technical field[0001]The present invention relates to the field of deep neural network, and more particularly to a human key identification method, device, intelligent terminal, and storage medium.Background technique[0002]With the development of computer technology, it is currently possible to detect key points of the human body from an image containing the human body. Human key points are also known as human gesture estimates, requires key parts of the body in a given picture, such as head, neck, shoulder, hand, and the like. Further, with the development of people, the task of the current human key detection is not only to obtain high-level semantic information containing human texture information, but also collects the degree of detection target and the surrounding environment, thereby achieving better recognition effect.[0003]In the prior art, the human key point detection is usually performed based on the deep neural network model, for example, the human key detection is perfo...
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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04
CPCG06V40/103G06V10/462G06N3/045G06F18/214
Inventor 曹晟言宏亮伍广彬卢瑶钟浩于波张华杨波梁兴伟杨卫国
Owner KONKA GROUP