Abstract: A new hybrid method to realise high-precision
distortion determination for optical ultra-precision 3D measurement
systems based on stereo cameras using active light projection is
introduced. It consists of two phases: the basic distortion
determination and the refinement. The refinement phase of the
procedure uses a plane surface and projected fringe patterns as
calibration tools to determine simultaneously the distortion of both
cameras within an iterative procedure. The new technique may be
performed in the state of the device “ready for measurement" which
avoids errors by a later adjustment. A considerable reduction of
distortion errors is achieved and leads to considerable improvements
of the accuracy of 3D measurements, especially in the precise
measurement of smooth surfaces.
Abstract: When reconstructing a scenario, it is necessary to
know the structure of the elements present on the scene to have an
interpretation. In this work we link 3D scenes reconstruction to
evolutionary algorithms through the vision stereo theory. We
consider vision stereo as a method that provides the reconstruction of
a scene using only a couple of images of the scene and performing
some computation. Through several images of a scene, captured from
different positions, vision stereo can give us an idea about the threedimensional
characteristics of the world. Vision stereo usually
requires of two cameras, making an analogy to the mammalian vision
system. In this work we employ only a camera, which is translated
along a path, capturing images every certain distance. As we can not
perform all computations required for an exhaustive reconstruction,
we employ an evolutionary algorithm to partially reconstruct the
scene in real time. The algorithm employed is the fly algorithm,
which employ “flies" to reconstruct the principal characteristics of
the world following certain evolutionary rules.