H. Kano, H. Fujioka, X. Chen, and T. Sato (Japan)
machine vision, motion recovery, perspective stereo vi sion, controllability.
We consider a problem of recovering motion of an ob ject moving in space under perspective observation. It is assumed that the motion equation is described by a linear system with unknown constant motion parame ters and that a single feature point on the object is per spectively 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, es tablished as a necessary and sufficient condition, turns out to be the controllability of a modified linear sys tem. 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.
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