公开(公告)号：US20220262024A1

公开(公告)日：2022-08-18

申请号：US17629373

申请日：2019-10-22

Applicant: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES

Inventor： Zhenan SUN ,  Hongwen ZHANG ,  Wanli OUYANG ,  Jie CAO

IPC: G06T7/55 ,  G06T17/10

Abstract: A reconstruction method of a three-dimensional (3D) human body model includes: acquiring, by a fully convolutional network (FCN) module, a global UVI map and a local UVI map of a body part according to a human body image (S1); estimating, by a first neural network, a camera parameter and a shape parameter of the human body model based on the global UVI map (S2); extracting, by a second neural network, rotation features of joints of a human body based on the local UVI map (S3); refining, by using a position-aided feature refinement strategy, the rotation features of the joints of the human body to acquire refined rotation features (S4); and estimating, by a third neural network, a pose parameter of the human body model based on the refined rotation features (S5). The reconstruction method achieves accurate and efficient reconstruction of the human body model, and improves robustness of pose estimation.