@inproceedings{67ac426ed4214034aae77a6b03386ee5,
title = "A novel robust statistical watermarking of 3D meshes",
abstract = "In this paper, we present a novel robust blind 3D mesh watermarking approach. We embed signature bits into the vertex norms distribution. At first, the robust source locations are extracted by using a salient point detector, based on the Auto Diffusion Function (ADF). Afterwards, the mesh is segmented into different regions according to the detected salient points. Then, the same watermark bits are embedded statistically into each region. The experimental results show the robustness of our method against cropping and other common attacks. Due to the stability of salient points, we can retrieve the watermarked region and extract the watermark. In addition, the performance of our method is also demonstrated on the minimal surface distortion in the embedding process.",
keywords = "3D watermarking, Fast marching method, Salient points, Statistical method",
author = "Nassima Medimegh and Samir Belaid and Mohamed Atri and Naoufel Werghi",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 6th International Workshop on Representations, Analysis and Recognition of Shape and Motion from Imaging Data, RFMI 2016 ; Conference date: 27-10-2016 Through 29-10-2016",
year = "2017",
doi = "10.1007/978-3-319-60654-5_3",
language = "British English",
isbn = "9783319606538",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "27--38",
editor = "Faten Chaieb and Faouzi Ghorbel and {Ben Amor}, Boulbaba",
booktitle = "Representations, Analysis and Recognition of Shape and Motion from Imaging Data - 6th International Workshop, RFMI 2016, Revised Selected Papers",
address = "Germany",
}