Parallel and efficient Boolean on polygonal solids
We present a novel framework which can efficiently evaluate approximate Boolean set operations for B-rep models by highly parallel algorithms. This is achieved by taking axis-aligned surfels of Layered Depth Images (LDI) as a bridge and performing Boolean operations on the structured points. As compared with prior surfel-based approaches, this paper has much improvement. Firstly, we adopt key-data pairs to store LDI more compactly. Secondly, robust depth peeling is investigated to overcome the bottleneck of layer-complexity. Thirdly, an out-of-core tiling technique is presented to overcome the limitation of memory. Real-time feedback is provided by streaming the proposed pipeline on the many-core graphics hardware.
layered depth images boolean operations depth peeling out-of-core cuda