Paper Info
Title
A Time Reversal Symmetry Based Real-time Optical Motion Capture Missing Marker Recovery Method
Abstract
This paper proposes a deep learning model based on time reversal symmetry for real-time recovery of continuous missing marker sequences in optical motion capture. This paper firstly uses time reversal symmetry of human motion as a constraint of the model. BiLSTM is used to describe the constraint and extract the bidirectional spatiotemporal features. This paper proposes a weight position loss function for model training, which describes the effect of different joints on the pose. Compared with the existing methods, the experimental results show that the proposed method has higher accuracy and good real-time performance.
Year
DOI
Venue
2022
10.1109/VRW55335.2022.00237
2022 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2022)
Keywords
DocType
Citations 
Human-centered computing, Human computer interaction(HCI), Interaction paradigms, Virtual reality
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Dongdong Weng12919.16
Yihan Wang200.34
Dong Li311548.55