Paper Info
Title
Watermark Embedder Optimization for 3D Mesh Objects Using Classification Based Approach
Abstract
This paper presents a novel 3D mesh watermarking scheme that utilizes a support vector machine(SVM) based classifier for watermark insertion. Artificial intelligence(AI)based approaches have been employed by watermarking algorithms for various host mediums such as images, audio, and video. However, AI based techniques are yet to be explored by researchers in the 3D domain for watermark insertion and extraction processes. Contributing towards this end, the proposed approach employs a binary SVM to classify vertices as appropriate or inappropriate candidates for watermark insertion. The SVM is trained with feature vectors derived from the curvature estimates of a 1-ring neighborhood of vertices taken from normalized 3D meshes. A geometry-based non-blind approach is used by the watermarking algorithm. The robustness of proposed technique is evaluated experimentally by simulating attacks such as mesh smoothing, cropping and noise addition.
Year
DOI
Venue
2010
10.1109/ICSAP.2010.83
ICSAP
Keywords
Field
DocType
mesh smoothing,watermarking algorithm,artificial intelligence,watermark embedder optimization,geometry-based non-blind approach,watermarking scheme,proposed technique,watermark insertion,binary svm,1-ring neighborhood,mathematical model,image classification,artificial intelligent,mesh generation,solid modeling,feature extraction,cropping,feature vector,support vector machines,watermarking,support vector machine
Computer vision,Feature vector,Digital watermarking,Polygon mesh,Pattern recognition,Computer science,Support vector machine,Feature extraction,Watermark,Smoothing,Artificial intelligence,Contextual image classification
Conference
ISBN
Citations 
PageRank 
978-1-4244-5725-0
1
0.37
References 
Authors
12
6
Name
Order
Citations
PageRank
Rakhi C. Motwani1154.51
Mukesh C. Motwani2164.60
Bobby D. Bryant3586.70
Frederick C. Harris Jr.454778.86
Akshata S. Agarwal510.37
Harris, F.C.642.34