Abstract
We consider a problem of recovering motion of an object moving in space under perspective observation. It is assumed that the motion equation is described by a linear system with unknown constant motion parameters and that a single feature point on the object is perspectively observed by two cameras. Then we analyze the identifiability of motion parameters from the stereo image data observed over an interval of time. The identifiability problem is solved by employing theories on linear dynamical systems, and the condition, established as a necessary and sufficient condition, turns out to be the controllability of a modified linear system. Such an analysis is essential when we develop and use any algorithms involving motion parameter identification. Finally, we include numerical results by employing the extended Kalman filter.
Original language | English |
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Article number | 412-224 |
Pages (from-to) | 103-108 |
Number of pages | 6 |
Journal | Proceedings of the IASTED International Conference on Modelling, Identification and Control |
Volume | 23 |
Publication status | Published - 2004 Dec 1 |
Externally published | Yes |
Event | Proceedings of the 23rd IASTED International Conference on Modelling, Identification, and Control - Grindelwald, Switzerland Duration: 2004 Feb 23 → 2004 Feb 25 |
Keywords
- Controllability
- Machine vision
- Motion recovery
- Perspective stereo vision
ASJC Scopus subject areas
- Software
- Modelling and Simulation
- Computer Science Applications