公开(公告)号：US20250022165A1

公开(公告)日：2025-01-16

申请号：US18755735

申请日：2024-06-27

Applicant: CHINA UNIVERSITY OF MINING AND TECHNOLOGY

Inventor： Xiaohu ZHAO ,  Xingyi YOU ,  Peng YOU ,  Sheng YE ,  Yong LIU

IPC: G06T7/73 ,  G06T5/10 ,  G06T5/20 ,  G06V10/44 ,  G06V10/80

Abstract: The present invention discloses an interactive behavior understanding method for posture reconstruction based on skeleton and image features. The steps are as follows: constructing and preprocessing the data set, extracting skeleton and image features, fusing and reconstructing these features, and conducting experimental evaluation and validation. This method retains the purity of skeleton features for human behavior information extraction and uses image features to retain effective environmental information, complementing the model feature information. Skeleton features are extracted using a graph convolution network, enhancing the relevance of input skeleton point information for accurate feature extraction. Effective image features are quickly and accurately extracted through the Vision Transformer network combined with a multi-head attention mechanism.