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Binary-Space-Partitioned Images for Resolving Image-Based Visibility
January-February 2004 (vol. 10 no. 1)
pp. 58-71

Abstract-We propose a novel 2D representation for 3D visibility sorting, the Binary-Space-Partitioned Image (BSPI), to accelerate real-time image-based rendering. BSPI is an efficient 2D realization of a 3D BSP tree, which is commonly used in computer graphics for time-critical visibility sorting. Since the overall structure of a BSP tree is encoded in a BSPI, traversing a BSPI is comparable to traversing the corresponding BSP tree. BSPI performs visibility sorting efficiently and accurately in the 2D image space by warping the reference image triangle-by-triangle instead of pixel-by-pixel. Multiple BSPIs can be combined to solve “disocclusion,” when an occluded portion of the scene becomes visible at a novel viewpoint. Our method is highly automatic, including a tensor voting preprocessing step that generates candidate image partition lines for BSPIs, filters the noisy input data by rejecting outliers, and interpolates missing information. Our system has been applied to a variety of real data, including stereo, motion, and range images.

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Index Terms:
Visibility sorting, binary space partitioning, image-based rendering, segmentation.
Citation:
Chi-Wing Fu, Tien-Tsin Wong, Wai-Shun Tong, Chi-Keung Tang, Andrew J. Hanson, "Binary-Space-Partitioned Images for Resolving Image-Based Visibility," IEEE Transactions on Visualization and Computer Graphics, vol. 10, no. 1, pp. 58-71, Jan.-Feb. 2004, doi:10.1109/TVCG.2004.1260758
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