公开(公告)号：US20250029261A1

公开(公告)日：2025-01-23

申请号：US18777953

申请日：2024-07-19

Applicant: Beijing Zitiao Network Technology Co., Ltd.

Inventor： Panwang PAN ,  Tao LIU ,  Cheng CHEN ,  Peng DAI ,  Meifeng XIAO

IPC: G06T7/20

Abstract: Embodiments of the present application provide a model training method and apparatus, and a device and a storage medium, and relate to the technical field of motion capture. The method includes: training a motion capture model according to a preset training set, wherein the motion capture model includes a time series prediction unit; performing, through a quantization node in the time series prediction unit, a quantization operation and an inverse quantization operation in sequence on model data passing through the quantization node; and adjusting a weight parameter of the time series prediction unit according to an update on a gradient of the time series prediction unit until the motion capture model converges, wherein the weight parameter includes a weight scaling parameter and a weight direction.

公开(公告)号：US20250076972A1

公开(公告)日：2025-03-06

申请号：US18821371

申请日：2024-08-30

Applicant: Beijing Zitiao Network Technology Co., Ltd.

Inventor： Peng DAI ,  Yang ZHANG

IPC: G06F3/01 ,  G06F3/0346 ,  G06N3/044 ,  G06T13/40 ,  G06T19/00

Abstract: The present disclosure provides a motion capture method and apparatus, an electronic device, and a storage medium. The method comprises: obtaining human inertial data collected by an extended reality device; and obtaining human pose information by inputting the human inertial data into a pre-trained motion capture model, where the motion capture model is obtained by training a neural network model based on a preset loss function; and the motion capture model comprises one or more of a neural network for predicting a human pose, a neural network for predicting global displacement information, a neural network for predicting a human bone parameter, and a classification network for predicting a human ground-stepping state.