A Method for Detecting Interaction between 3D Hands and Unknown Objects in RGB Video. Issue 1 (April 2021)

• Record Type: Journal Article
• Authors: Wu, Yankun; Wang, Peipei; Wang, Xin; Liu, Guanqun; Zhao, Lin; Xiang, Ji
• Is Part Of: Journal of physics. Volume 1873:Issue 1(2021)
• Publication Date: 2021-04
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1873/1/012038
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: We propose a model that can extract 3D position of hand and object in per-frame of RGB videos through a single feed-forward neural network and a zero-shot learning classifier, and understand unknown hand-object interactions in the entire video through an interactive temporal module. The process is trained end-to-end, without depth images or annotated coordinates as input, which has good application prospects in real life.