Problems in robot vision such as object manipulation and trajectory
planning require that multiple views of data (e.g. time series, multiple
sensor, etc.) be integrated into a consistent interpretation of the
scene. Our approach to this problem is based on a surface reconstruction
algorithm that combines information from different viewpoints. It does
so without explicitly computing correspondence and without invoking a
global rigidity assumption. Motion parameters (rotations and
translations) are recovered locally under the assumption that the
curvature structure at a point on a surface varies slowly under
transformation. The recovery problem can thus be posed as finding the
set of motion parameters that preserves curvature across adjacent
views. This might be viewed as a temporal form of the curvature
consistency constraint used in image and surface reconstruction.
To reconstruct a 3-D surface from a sequence of overlapping range
images, one can attempt to apply local motion estimates to successive
pairs of images in pointwise fashion. However this approach does not
work well in practice because estimates computed * locally* are
subject to the effects of noise and quantization error. This problem is
addressed by invoking a second constraint that concerns the properties
of physical surfaces. The motions of adjacent points are coupled through
the surface, where the degree of coupling is proportional to surface
rigidity. We interpret this constraint to mean that motion varies
smoothly from point to point and attempt to regularize local estimates
by enforcing smooth variation of the motion parameters. This is
accomplished by applying a regularizing filter to the local estimates as
a second stage of processing.
By combining curvature and motion consistency constraints we have been
able to derive a multiple view reconstruction algorithm that can
accurately reconstruct three-dimensional surfaces from a sequence of
range images.

G. Soucy, F.P. Ferrie

View Registration using Curvature and Motion Consistency

Mon Nov 13 10:43:02 EST 1995