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Daniel Cotting, Tim Weyrich, Mark Pauly, Markus Gross, Robust Watermarking of Point-Sampled Geometry, Shape Modeling International 2004
Abstract:
We present a new scheme for digital watermarking of
point-sampled geometry based on spectral analysis. By
extending existing algorithms designed for polygonal data
to unstructured point clouds, our method is particularly
suited for scanned models, where the watermark can be
directly embedded in the raw data obtained from the 3D
acquisition device. To handle large data sets efficiently, we
apply a fast hierarchical clustering algorithm that partitions
the model into a set of patches. Each patch is mapped
into the space of eigenfunctions of an approximate Laplacian
operator to obtain a decomposition of the patch surface
into discrete frequency bands. The watermark is then
embedded into the low frequency components to minimize
visual artifacts in the model geometry. During extraction,
the target model is resampled at optimal resolution using
an MLS projection. After extracting a watermark from this
model, the corresponding bit stream is analyzed using statistical
methods based on correlation. We have applied our
method to a number of point-sampled models of different
geometric and topological complexity. These experiments
show that our watermarking scheme is robust against
numerous attacks, including low-pass filtering, resampling,
affine transformations, cropping, additive random
noise, and combinations of the above.
Bibtex:
@inproceedings{cwpg-rwpsg-04,
author = {Daniel Cotting and Tim Weyrich and Mark Pauly and Markus Gross },
title = {Robust Watermarking of Point-Sampled Geometry},
booktitle = {Shape Modeling International},
year = {2004},
}
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