Three-dimensional human body posture estimation method based on feature fusion and sample enhancement
A technology of feature fusion and human body posture, applied in the field of computer vision, can solve the problems of imperfect 3D posture recognition analysis, difficulty in extending to daily life and application, and high cost, so as to enrich machine learning theory and methods and expand machine learning theory and the effect of the method
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[0048] The implementation of the present invention will be described in detail below in conjunction with the drawings and examples, so that the present invention can fully understand and implement the process of how to apply technical means to solve technical problems and achieve technical effects in the present invention.
[0049] The invention discloses a three-dimensional human pose estimation method based on feature fusion and sample enhancement, comprising the following steps:
[0050] Step 1: Part classification and pixel regression
[0051] 1.1 In this embodiment, the human body sample data set in the COCO data set is used, with a total of 50,000 pictures. The pictures in the data set contain target human bodies with complex scenes, different shapes, and different sizes; the training set is divided into 48,000 pictures, and the test set is 2,000 pictures.
[0052] 1.2 Divide the human body into several different body parts according to the three-dimensional model, and us...
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