The advantages of digital media such as the Internet and CD-ROMs lie in the fact that their contents are easy to duplicate, edit, and distribute. These advantages, however, are double-edged swords, because they also facilitate unauthorized use of such contents. Data embedding, which places information into the contents themselves, is an approach to address this issue. Embedded information can be used, for example, for copyright protection, theft deterrence, and inventory.This paper discusses our work on embedding data into three-dimensional (3D) polygonal models of geometry. Given objects consisting of points, lines, polygons, or curved surfaces, the data embedding algorithms described in this paper produce polygonal models with data embedded. Data are placed into 3D polygonal models by modifying either their vertex coordinates, their vertex topology (connectivity), or both.A brief review of related work and a description of the requirements of data embedding is followed by a discussion of where, and by what fundamental methods, data can be embedded into 3D polygonal models. The paper then presents data-embedding algorithms, with examples, based on these fundamental methods.
This paper presents a robust watermarking algorithm with informed detection for 3D polygonal meshes. The algorithm is based on our previous algorithm [22] that employs mesh‐spectral analysis to modify mesh shapes in their transformed domain. This paper presents extensions to our previous algorithm so that (1) much larger meshes can be watermarked within a reasonable time, and that (2) the watermark is robust against connectivity alteration (e.g., mesh simplification), and that (3) the watermark is robust against attacks that combine similarity transformation with such other attacks as cropping, mesh simplification, and smoothing. Experiment showed that our new watermarks are resistant against mesh simplification and remeshing combined with resection, similarity transformation, and other operations..
Artículo de publicación ISI.Non-rigid 3D shape retrieval has become an active and important research topic in content-based 3D object retrieval. The aim of this paper is to measure and compare the performance of state-of-the-art methods for non-rigid 3D shape retrieval. The paper develops a new benchmark consisting of 600 non-rigid 3D watertight meshes, which are equally classified into 30 categories, to carry out experiments for 11 different algorithms, whose retrieval accuracies are evaluated using six commonly utilized measures. Models and evaluation tools of the new benchmark are publicly available on our web site [1]. (C) 2012 Elsevier Ltd. All rights reservedChina Postdoctoral Science Foundation (GrantNo.2012M510274),the SIMA program, the Shape Metrology IMS, and Fondecyt (Chile) Project 111011
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