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Semantics-Guided Human Motion Modeling In Virtual Reality Environment, Matthew Korban
Semantics-Guided Human Motion Modeling In Virtual Reality Environment, Matthew Korban
LSU Doctoral Dissertations
Human Motion Modeling is essential in Computer Animation and Human-Computer Interaction. This dissertation studies how to enhance the speed and robustness of Human Motion Modeling in Virtual Reality (VR) environments. Specifically, we aim to design a pipeline to effectively capture and use semantic action information to guide the motion capturing from users in physical worlds and its transfer onto digital avatars in VR environments. To recognize the user's action, we first proposed a new Dynamic Directed Graph Convolutional Network (DDGCN) to model spatial and temporal features from users' skeletal representations. The DDGCN consists of several dynamic feature modeling modules to …