Integrated treatment of matching and measurement errors for robust model-based motion tracking

A system is described for real-time motion tracking of 3-D objects, including those with variable internal parameters. Unlike most previous work on model-based motion tracking, this system provides for the integrated treatment of matching and measurement errors during motion tracking. These two sources of error have very different distributions and must be handled by separate computational mechanisms. These errors can be treated in an integrated way by using the computation of variance in predicted feature measurements to greatly decrease the amount of search required for subsequent matching. In return, the search process is used to eliminate the need to treat outliers during the analysis of measurement errors. The resulting system can robustly track models with many degrees of freedom while running on relatively inexpensive hardware. These same techniques can be used to speed verification during model-based recognition, and they point the way to merging of systems for recognition and motion tracking