Abstract
We consider the problem of automatically generating sequences of structured-light patterns for active stereo triangulation of a static scene. Unlike existing approaches that
use predetermined patterns and reconstruction algorithms
tied to them, we generate patterns on the fly in response
to generic specifications: number of patterns, projectorcamera arrangement, workspace constraints, spatial frequency content, etc. Our pattern sequences are specifically
optimized to minimize the expected rate of correspondence
errors under those specifications for an unknown scene, and
are coupled to a sequence-independent algorithm for perpixel disparity estimation. To achieve this, we derive an
objective function that is easy to optimize and follows from
first principles within a maximum-likelihood framework. By
minimizing it, we demonstrate automatic discovery of pattern sequences, in under three minutes on a laptop, that can
outperform state-of-the-art triangulation techniques.