Watermaking three-dimensional polygonal models
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Digital Steganography: Hiding Data within Data
IEEE Internet Computing
Edgebreaker: Connectivity Compression for Triangle Meshes
IEEE Transactions on Visualization and Computer Graphics
Watermarking 3D polygonal meshes in the mesh spectral domain
GRIN'01 No description on Graphics interface 2001
Robust Watermarking of Point-Sampled Geometry
SMI '04 Proceedings of the Shape Modeling International 2004
Data hiding on 3D polygonal meshes
Proceedings of the 2004 workshop on Multimedia and security
Watermarking a 3D Shape Model Defined as a Point Set
CW '04 Proceedings of the 2004 International Conference on Cyberworlds
Blind Robust Watermarking Schemes for Copyright Protection of 3D Mesh Objects
IEEE Transactions on Visualization and Computer Graphics
A high-capacity steganographic approach for 3D polygonal meshes
The Visual Computer: International Journal of Computer Graphics
An adaptive steganographic algorithm for 3D polygonal meshes
The Visual Computer: International Journal of Computer Graphics
A robust spectral approach for blind watermarking of manifold surfaces
Proceedings of the 10th ACM workshop on Multimedia and security
A High Capacity 3D Steganography Algorithm
IEEE Transactions on Visualization and Computer Graphics
Technical section: Steganography on point-sampled geometry
Computers and Graphics
Blind robust 3-D mesh watermarking based on oblate spheroidal harmonics
IEEE Transactions on Multimedia
A novel semi-blind-and-semi-reversible robust watermarking scheme for 3D polygonal models
The Visual Computer: International Journal of Computer Graphics
An improved data hiding approach for polygon meshes
The Visual Computer: International Journal of Computer Graphics
Data hiding on 3-D triangle meshes
IEEE Transactions on Signal Processing
An Oblivious Watermarking for 3-D Polygonal Meshes Using Distribution of Vertex Norms
IEEE Transactions on Signal Processing
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This paper presents a high-capacity data-hiding approach for polygonal meshes using maximum expected level tree based on a message probability model. While embedding/extracting a bitstring for a primitive, a maximum expected level tree is built level-by-level for all remaining primitives arranged in a reference order. At each level, the number of leaf nodes in one subtree is determined based on the occurrence probability of the interested event for the next message bit from the proposed message probability model, such that the traversal path from the root to the embedding/extracting primitive (leaf node) is as long as possible. Moreover, the traversal path represents the embedded/extracted message. Given an embedding message, the 0-bit and 1-bit run-length histograms on which the proposed message probability model is based are computed initially and updated after each embedding/extracting step. When extracting, the histograms are extracted first from the stego model and then used to extract the message from each primitive. The capacity of our approach depends on the run-length histograms of a given embedding message. The experimental results show that our capacity is larger than that of previous methods, the improvements in capacity for text-based, binary-based, and compressed-based message types are approximately 18.21%, 44.79%, and 14.86%, respectively. Moreover, as a permutation steganography approach, the stego model is distortion-free, and the embedded message is imperceptible and robust to geometric affine transformations.