Abstract
This article considers the fundamental task of 3-D tracking as a direct image registration problem. 3-D tracking consists in continuously recovering the camera motion in the Euclidean space. Direct methods refer to those that exploit the pixel intensities without intermediate steps, e.g., no extraction of image features. This work presents new photogeometric transformation models and nonlinear optimization methods for directly registering calibrated central omnidirectional images of planar objects. The proposed approach simultaneously reconstructs the camera motion, the planar structure, and the illumination variations so as to perform the tracking. Experimental results show that 3-D tracking can indeed be highly robust and accurate even for this type of vision systems.
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