Abstract
Recent advances in 3D scanning technologies have enabled us to acquire large scale point-clouds data rapidly. Point-based representation has been introduced as a versatile and powerful graphics primitive. This paper proposes an adaptive rendering algorithm for large scale point models. The algorithm first subdivide the target model into multiple patches in the preprocess. A hierarchical structure is built for each patch and then converted into a linear binary tree. During rendering, the model is processed patch by patch. Fast visibility decision is made to cull invisible patches. Visible patches are displayed in graphics processing units (GPU) by choosing appropriate rendering mode, i.e, a distance-dependent strategy. Our algorithm takes full advantage of GPU and effectively balances the workload between CPU and GPU. We also propose a fast compression/decompression technique which achieves 8 times compression ratio. Experimental results demonstrates high performance and image quality rendering for large scale 3D scanning models in consumer PCs.
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© 2004 Springer-Verlag Berlin Heidelberg
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Dong, Z., Chen, W., Zhang, L., Peng, Q. (2004). Balancing CPU and GPU: Real-Time Visualization of Large Scale 3D Scanning Models. In: Jin, H., Pan, Y., Xiao, N., Sun, J. (eds) Grid and Cooperative Computing - GCC 2004 Workshops. GCC 2004. Lecture Notes in Computer Science, vol 3252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30207-0_87
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DOI: https://doi.org/10.1007/978-3-540-30207-0_87
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23578-1
Online ISBN: 978-3-540-30207-0
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