Perspective dynamical systems arise in machine vision, and the essential problem in such a system is how to determine any unknown states and/or any unknown parameters from its perspective observation. Considering simple perspective dynamical systems, we study the state observability and the parameter identifiability of such systems, using the differential geometric method, that is, the observability rank condition, which has been developed for general nonlinear systems, and present various necessary and/or sufficient conditions for observability and/or identifiability.
|Number of pages||6|
|Journal||Proceedings of the IEEE Conference on Decision and Control|
|State||Published - Dec 2000|