A Dynamic 3D Human Model using Hybrid 2D-3D Representations inHierarchical PCA Space
Eng-Jon Ong, Shaogang Gong · 1999
We propose a novel framework for a hybrid 2D-3D dynamic human model with which robust matching and tracking of a 3D skeleton model of a human body among multiple views can be performed. We describe a method that measures the image ambiguity at each view. The 3D skeleton model and the correspondence between the model and its 2D images are learnt using hierarchical principal component analysis. Tracking in individual views is performed based on CONDENSATION.