ACM Transactions on Graphics (TOG)
Geometry-Based Watermarking of 3D Models
IEEE Computer Graphics and Applications
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
A watermarking for 3D mesh using the patch CEGIs
Digital Signal Processing
Content-Based 3D Object Retrieval
IEEE Computer Graphics and Applications
A New Watermarking Method for 3D Models Based on Integral Invariants
IEEE Transactions on Visualization and Computer Graphics
Information-theoretic hashing of 3D objects using spectral graph theory
Expert Systems with Applications: An International Journal
A novel image hash algorithm resistant to print-scan
Signal Processing
Blind robust 3-D mesh watermarking based on oblate spheroidal harmonics
IEEE Transactions on Multimedia
A secure and robust hash-based scheme for image authentication
Signal Processing
Fragility analysis of adaptive quantization-based image hashing
IEEE Transactions on Information Forensics and Security
DELOS'07 Proceedings of the 1st international conference on Digital libraries: research and development
CAD drawing watermarking scheme
Digital Signal Processing
Perceptual image hashing based on virtual watermark detection
IEEE Transactions on Image Processing
Technical Section: Robust and blind mesh watermarking based on volume moments
Computers and Graphics
Perceptual hashing of video content based on differential block similarity
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
An Oblivious Watermarking for 3-D Polygonal Meshes Using Distribution of Vertex Norms
IEEE Transactions on Signal Processing
Robust video hashing based on radial projections of key frames
IEEE Transactions on Signal Processing - Part II
Unicity Distance of Robust Image Hashing
IEEE Transactions on Information Forensics and Security - Part 1
Robust and Secure Image Hashing via Non-Negative Matrix Factorizations
IEEE Transactions on Information Forensics and Security - Part 1
A clustering based approach to perceptual image hashing
IEEE Transactions on Information Forensics and Security
Robust and secure image hashing
IEEE Transactions on Information Forensics and Security
Spatio–Temporal Transform Based Video Hashing
IEEE Transactions on Multimedia
Watermarking Digital 3-D Volumes in the Discrete Fourier Transform Domain
IEEE Transactions on Multimedia
Watermarking mesh-based representations of 3-D objects using local moments
IEEE Transactions on Image Processing
Perceptual Image Hashing Via Feature Points: Performance Evaluation and Tradeoffs
IEEE Transactions on Image Processing
MPEG-7 visual shape descriptors
IEEE Transactions on Circuits and Systems for Video Technology
Robust Video Fingerprinting for Content-Based Video Identification
IEEE Transactions on Circuits and Systems for Video Technology
Key-dependent 3D model hashing for authentication using heat kernel signature
Digital Signal Processing
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3D model hashing can be very useful for the authentication, indexing, copy detection, and watermarking of 3D content, in a manner similar to image hashing. 3D models can be easily modified by graphics editing while preserving the geometric shape, and the modeling representations are not regular, unlike an image with a fixed pixel array. A 3D model must be authenticated, indexed, or watermarked while being robust against graphics attacks and irregular representations. For these purposes, this paper presents a 3D mesh model hashing based on object feature vectors with the robustness, security, and uniqueness. The proposed hashing groups the distances from feature objects with the highest surface area in a 3D model that consists of a number of objects, permutes indices of groups in feature objects, and generates a binary hash through the binarization of feature values that are calculated by two combinations of group values and a random key. The robustness of a hash can be improved by group coefficients that are obtained from the distribution of vertex distances in feature objects, and the security and uniqueness can be improved by both the permutation of groups, feature vectors, and random key. Experimental results verified that the proposed hashing is robust against various perceptual geometrical and topological attacks and has the security and uniqueness of a hash.