M.L. Molenaar
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Sparse Voxel Directed Acyclic Graphs (SVDAGs) have proven to be an efficient data structure for storing sparse binary voxel scenes. The SVDAG exploits repeating geometric patterns; which can be improved when considering mirror symmetries. We extend the previous work by providing a generalized framework to efficiently involve additional types of transformations and propose a novel translation matching for even more geometry reuse. Our new data structure is stored using a novel pointer encoding scheme to achieve a practical reduction in memory usage.
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Sparse Voxel Directed Acyclic Graphs (SVDAGs) have proven to be an efficient data structure for storing sparse binary voxel scenes. The SVDAG exploits repeating geometric patterns; which can be improved when considering mirror symmetries. We extend the previous work by providing a generalized framework to efficiently involve additional types of transformations and propose a novel translation matching for even more geometry reuse. Our new data structure is stored using a novel pointer encoding scheme to achieve a practical reduction in memory usage.
Despite the exponential growth in computational power, displaying highly detailed scenes remains challenging due to memory and performance limitations. One method of representing scenes is using voxels; the tiny cubic cells of a regular grid. In this dissertation, we are concerned with the Sparse Voxel Directed Acyclic Graph (SVDAG) data structure and how it can be used to improve large-scene rendering. The SVDAG is a hierarchical data structure that aims to reduce memory usage by identifying geometric redundancy. We address several challenges regarding this type of voxel compression.
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Despite the exponential growth in computational power, displaying highly detailed scenes remains challenging due to memory and performance limitations. One method of representing scenes is using voxels; the tiny cubic cells of a regular grid. In this dissertation, we are concerned with the Sparse Voxel Directed Acyclic Graph (SVDAG) data structure and how it can be used to improve large-scene rendering. The SVDAG is a hierarchical data structure that aims to reduce memory usage by identifying geometric redundancy. We address several challenges regarding this type of voxel compression.
A Sparse Voxel Directed Acyclic Graph (SVDAG) is an efficient representation to display and store a highly-detailed voxel representation in a very compact data structure. Yet, editing such a high-resolution scene in real-time is challenging. Existing solutions are hybrid, involving the CPU, and are restricted to small local modifications. In this work, we address this bottleneck and propose a solution to perform edits fully on the graphics card, enabled by dynamic GPU hash tables. Our framework makes large editing operations possible, such as 3D painting, at real-time frame rates.
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A Sparse Voxel Directed Acyclic Graph (SVDAG) is an efficient representation to display and store a highly-detailed voxel representation in a very compact data structure. Yet, editing such a high-resolution scene in real-time is challenging. Existing solutions are hybrid, involving the CPU, and are restricted to small local modifications. In this work, we address this bottleneck and propose a solution to perform edits fully on the graphics card, enabled by dynamic GPU hash tables. Our framework makes large editing operations possible, such as 3D painting, at real-time frame rates.
Sparse Voxel Directed Acyclic Graphs (SVDAGs) are an efficient solution for storing high-resolution voxel geometry. Recently, algorithms for the interactive modification of SVDAGs have been proposed that maintain the compressed geometric representation. Nevertheless, voxel attributes, such as colours, require an uncompressed storage, which can result in high memory usage over the course of the application. The reason is the high cost of existing attribute-compression schemes which remain unfit for interactive applications. In this paper, we introduce two attribute compression methods (lossless and lossy), which enable the interactive editing of compressed high-resolution voxel scenes including attributes.
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Sparse Voxel Directed Acyclic Graphs (SVDAGs) are an efficient solution for storing high-resolution voxel geometry. Recently, algorithms for the interactive modification of SVDAGs have been proposed that maintain the compressed geometric representation. Nevertheless, voxel attributes, such as colours, require an uncompressed storage, which can result in high memory usage over the course of the application. The reason is the high cost of existing attribute-compression schemes which remain unfit for interactive applications. In this paper, we introduce two attribute compression methods (lossless and lossy), which enable the interactive editing of compressed high-resolution voxel scenes including attributes.
We present a method for improving batched ray traversal as was presented by Pharr et al. [PKGH97]. We propose to use conservative proxy geometry to more accurately determine whether a ray has a possibility of hitting any geometry that is stored
on disk. This prevents unnecessary disk loads and thus reduces the disk bandwidth.
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We present a method for improving batched ray traversal as was presented by Pharr et al. [PKGH97]. We propose to use conservative proxy geometry to more accurately determine whether a ray has a possibility of hitting any geometry that is stored
on disk. This prevents unnecessary disk loads and thus reduces the disk bandwidth.