Three-dimensional human body posture estimation method and computer readable storage medium

Abstract

The invention provides a three-dimensional human body posture estimation method and a computer readable storage medium. The method comprises the following steps: acquiring a single-person image from an original image by adopting a human body detection network and carrying out standardization processing on the single-person image; predicting two-dimensional coordinates of the key points from the single-person image by using a two-dimensional attitude estimation method; generating a three-dimensional coordinate from the two-dimensional coordinate, including: predicting a first three-dimensional coordinate of the key point by using a three-dimensional attitude generator; performing symmetric processing on the two-dimensional coordinates according to a symmetric structure of a human body joint, and predicting second three-dimensional coordinates of the key points by using a three-dimensional attitude generator; enabling the first three-dimensional coordinate and the second three-dimensional coordinate to respectively calculate difference values with the corresponding labels, the sum of the results bing used for back propagation, and obtaining three-dimensional human body posture estimation. A connection relation and a symmetric relation between key points of a human body are fully utilized, and the purpose of optimizing a prediction result can be achieved; and meanwhile, on the basis of an original data set, the expansion of training data is realized, and the robustness of the model is enhanced.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a method for estimating a three-dimensional human posture and a computer-readable storage medium. Background technique [0002] It is a very valuable research direction in the field of computer vision to estimate the human body pose on a two-dimensional RGB image containing a portrait, that is, to output the coordinate position of the key points of the designated human body according to the image information. The detection results of human pose estimation can further serve many industrial fields such as human body reconstruction, human-computer interaction, behavior recognition, virtual reality, game modeling, etc., and have been applied to many products. Compared with two-dimensional attitude, the result of three-dimensional attitude estimation can provide higher-dimensional and richer information in application, and has broad application prospects. Therefore, in recent...

AI Technical Summary

Problems solved by technology

[0011] In order to solve the existing problems, the present invention provides a three-dimensional human pose estimation method and a computer-readable storage medium

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