Using an adaptive VAR model for motion prediction in 3D hand tracking
Date
2008
Authors
Chik, Desmond
Trumpf, Jochen
Schraudolph, Nic
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
A robust VAR-based (vector autoregressive) model is introduced for motion prediction in 3D hand tracking. This dynamic VAR motion model is learned in an online manner. The kinematic structure of the hand is accounted for in the form of constraints when solving for the parameters of the VAR model. Also integrated into the motion prediction model are adaptive weights that are optimised according to the reliability of past predictions. Experiments on synthetic and real video sequences show a substantial improvement in tracking performance when the robust VAR motion model is used. In fact, utilising the robust VAR model allows the tracker to handle fast out-of-plane hand movement with severe self-occlusion.
Description
Keywords
Keywords: 3D hand tracking; Adaptive weights; Auto-regressive; Hand movement; Kinematic structures; Motion models; Motion prediction; Out-of-plane; Real video sequences; Self occlusion; Tracking performance; Face recognition; Mathematical models; Three dimensional;
Citation
Collections
Source
Proceedings of International Conference on Automatic Face and Gesture Recognition 2008
Type
Conference paper