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Raycasting implementations require that the connectivity
between the cells of the dataset to be explicitly computed
and kept in memory. This constitutes a huge obstacle
for obtaining realtime rendering for very large models.
In this paper, we address this problem by introducing
a new implementation of the raycasting algorithm for irregular
datasets. Our implementation optimizes the memory
usage of past implementations by exploring ray coherence.
The idea is to keep in main memory the information of
the faces traversed by the ray cast through every pixel under
the projection of a visible face. Our results show that
exploring pixel coherence reduces considerably the memory
usage, while keeping the performance of our algorithm
competitive with the fastest previous ones.
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