Title :
Adaptive Out-of-Core Simplification of Large Point Clouds
Author :
Du, Xiaohui ; Yin, Baocai ; Kong, Dehui
Author_Institution :
Beijing Univ. of Technol., Beijing
Abstract :
With the increasing of data complexity, the needs for out-of-core simplification become evident. However, most of the existing point-based simplification algorithms adopt in-core scheme. We present an adaptive out-of-core algorithm for simplifying point-sampled models. Our approach uses quadric matrix to analyze the detailed regions of the initial simplified model that generated by an out-of-core uniform clustering. And then we use point-pair contraction to further simplify the flat regions and point-split to refine the detailed regions. Since the algorithm is input insensitive, it obtains high quality with low memory requirement.
Keywords :
adaptive signal processing; pattern clustering; signal detection; adaptive out of core simplification; data complexity; large point clouds; point pair contraction; quadric matrix; uniform clustering; Clouds; Clustering algorithms; Computer science; Educational institutions; Geometry; Iterative algorithms; Laboratories; Sampling methods; Surface fitting; Topology;
Conference_Titel :
Multimedia and Expo, 2007 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-1016-9
Electronic_ISBN :
1-4244-1017-7
DOI :
10.1109/ICME.2007.4284931