A Flexible Pipeline for the Optimization of CSG Trees
This work addresses the challenge of improving human-controlled editing of 3D geometry representations for users in computer graphics and CAD, but it is incremental as it builds on existing optimization methods.
The paper tackles the problem of optimizing CSG trees for editability by proposing a flexible pipeline that includes redundancy removal and decomposition, and introduces a new quantitative measure for editability. The result is a systematic comparison of methods and demonstration of using the measure as a constraint in optimization.
CSG trees are an intuitive, yet powerful technique for the representation of geometry using a combination of Boolean set-operations and geometric primitives. In general, there exists an infinite number of trees all describing the same 3D solid. However, some trees are optimal regarding the number of used operations, their shape or other attributes, like their suitability for intuitive, human-controlled editing. In this paper, we present a systematic comparison of newly developed and existing tree optimization methods and propose a flexible processing pipeline with a focus on tree editability. The pipeline uses a redundancy removal and decomposition stage for complexity reduction and different (meta-)heuristics for remaining tree optimization. We also introduce a new quantitative measure for CSG tree editability and show how it can be used as a constraint in the optimization process.