Choosing consistent constraints for beautification of reverse engineered geometric models
Boundary representation models reconstructed from 3D range data suffer from various inaccuracies caused by noise in the data and the model building software. Such models can be improved in a beautification step, which finds geometric regularities approximately present in the model and imposes a consistent subset of them on the model. Methods to select regularities consistently such that they are likely to represent the original, ideal design intent are presented. Efficiency during selection is achieved by considering degrees of freedom to analyse the solvability of constraint systems representing the regularities (without actually solving them). Priorities are used to select regularities in case of inconsistencies. The selected set of constraints is solved numerically and an improved model is rebuilt from the solution. Experiments show that the presented methods can beautify models by selecting consistent regularities and enforcing major intended regularities.
beautification reverse engineering geometric constraints degrees of freedom analysis