| Abstract | We investigate the relationship between camera design and the problem of recovering the motion andstructure of a scene from video data. The visual information that could possibly be obtained is described
by the plenoptic function. A camera can be viewed as a device that captures a subset of this function,
that is, it measures some of the light rays in some part of the space. The information contained in the
subset determines how difficult it is to solve subsequent interpretation processes. By examining the
differential structure of the time varying plenoptic function we relate different known and new camera
models to the spatio-temporal structure of the observed scene. This allows us to define a hierarchy
of camera designs, where the order is determined by the stability and complexity of the computations
necessary to estimate structure and motion. At the low end of this hierarchy is the standard planar
pinhole camera for which the structure from motion problem is non-linear and ill-posed. At the high
end is a camera, which we call the full field of view polydioptric camera, for which the problem is linear
and stable. In between are multiple-view cameras with large fields of view which we have built, as well
as catadioptric panoramic sensors and other omni-directional cameras. We develop design suggestions
for the polydioptric camera, and based upon this new design we propose a linear algorithm for ego-
motion estimation, which in essence combines differential motion estimation with differential stereo.
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