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Compression of Dense and Regular Point Clouds
Author(s) -
Merry Bruce,
Marais Patrick,
Gain James
Publication year - 2006
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2006.00993.x
Subject(s) - compression (physics) , enhanced data rates for gsm evolution , point cloud , spanning tree , data compression ratio , algorithm , data compression , computer science , point (geometry) , mathematics , range (aeronautics) , tree (set theory) , geometry , image compression , artificial intelligence , combinatorics , image (mathematics) , image processing , materials science , composite material
We present a simple technique for single‐rate compression of point clouds sampled from a surface, based on a spanning tree of the points. Unlike previous methods, we predict future vertices using both a linear predictor, which uses the previous edge as a predictor for the current edge, and lateral predictors that rotate the previous edge 90° left or right about an estimated normal . By careful construction of the spanning tree and choice of prediction rules, our method improves upon existing compression rates when applied to regularly sampled point sets, such as those produced by laser range scanning or uniform tesselation of higher‐order surfaces. For less regular sets of points, the compression rate is still generally within 1.5 bits per point of other compression algorithms .