@inproceedings{c203f2c3d4e54d4d90003737ef623cfd,
title = "3D mesh robust watermarking technique for ownership protection",
abstract = "A 3d mesh blind optimized watermarking technique is proposed in this paper. The technique relies on the displacement process of the vertices locations depending on the modification of the variances of the vertices's norms. Statistical analysis were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduces in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. Experimental results showed that the approach is robust in terms of both the perceptual and the quantitative qualities. Moreover, it was also robust against both the geometry and connectivity attacks.",
keywords = "Laplacian Smoothing, Local Roughness, Mesh Object, Watermarking",
author = "Alenizi, \{Farhan A.\} and Fadi Kurdahi and Ahmed Eltawil",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 ; Conference date: 29-10-2017 Through 01-11-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ACSSC.2017.8335170",
language = "English",
series = "Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "217--222",
editor = "Matthews, \{Michael B.\}",
booktitle = "Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017",
address = "United States",
}