Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
The design and analysis of spatial data structures
The design and analysis of spatial data structures
Efficient ray tracing of volume data
ACM Transactions on Graphics (TOG)
A rapid hierarchical radiosity algorithm
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Hierarchical splatting: a progressive refinement algorithm for volume rendering
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Octrees for faster isosurface generation
ACM Transactions on Graphics (TOG)
Hierarchical Z-buffer visibility
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Octree-based decimation of marching cubes surfaces
Proceedings of the 7th conference on Visualization '96
Programming with POSIX threads
Programming with POSIX threads
On visible surface generation by a priori tree structures
SIGGRAPH '80 Proceedings of the 7th annual conference on Computer graphics and interactive techniques
Data-parallel mesh connected components labeling and analysis
EG PGV'11 Proceedings of the 11th Eurographics conference on Parallel Graphics and Visualization
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Multi-resolution methods are widely used in scientific visualization, image processing, and computer graphics. While many applications only require an one-time construction of these data-structures which can be done in a pre-process, this pre-process can take a significant amount of time. Considering large datasets, this time consumption can range from several minutes up to several hours, especially if this preprocess is frequently needed. Furthermore, numerous new applications, such as visibility queries, arise which often need a dynamic reconstruction of a scene database. In this paper, we address several problems of the construction or reconstruction of recursive tree hierarchies in parallel. In particular, we focus on parallel dynamic memory allocation and the associated synchronization overhead.