BMVC 2004, Kingston, 7th-9th Sept, 2004

Recovering Camera Pose from Omni-directional Images
A. Wan, A. Siu and R. Lau (City University of Hong Kong)

Omni-directional images are widely used in image-based walkthrough
applications, in which camera pose recovery is one of the initial and
important processes. Existing methods may recover camera pose of omnidirectional
images from lines. However, it may not work well when there is
insufficient scene structure in the images. In addition, existing methods
involve non-linear optimization and iterative algorithms, which may lead to
the convergence problem and high computational cost.
In this paper, we propose an automatic camera pose recovery method for
a network of omni-directional images. Our method only requires 2D point
correspondences as input. We divide the problem into the orientation and
position components, and determine them separately. The relative rotations
between adjacent views are aggregated to estimate the global orientations.
An algorithm is developed to adjust the rotations for avoiding global
inconsistency and error accumulation. For position recovery, we have
derived a linear global formulation for establishing correspondences and
positions among multiple views. Globally optimized positions can be
obtained simply by solving the formulation. We demonstrate the performance
of our method with some experiments.
(pdf article)

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