Fragile Watermarking of 3D Models Using Genetic Algorithms

This paper describes a novel algorithm for fragile watermarking of 3D models. Fragile watermarking requires detection of even minute intentional changes to the 3D model along with the location of the change. This poses a challenge since inserting random amount of watermark in all the vertices of the model would generally introduce perceptible distortion. The proposed algorithm overcomes this challenge by using genetic algorithm to modify every vertex location in the model so that there is no perceptible distortion. Various experimental results are used to justify the choice of the genetic algorithm design parameters. Experimental results also indicate that the proposed algorithm can accurately detect location of any mesh modification.

An Eigen-Normal Approach for 3D Mesh Watermarking Using Support Vector Machines

The use of support vector machines （SVM） for watermarking of 3D mesh models is investigated. SVMs have been widely explored for images, audio, and video watermarking but to date the potential of SVMs has not been explored in the 3D watermarking domain. The proposed approach utilizes SVM as a binary classifier for the selection of vertices for watermark embedding. The SVM is trained with feature vectors derived from the angular difference between the eigen normal and surface normals of a 1-ring neighborhood of vertices taken from normalized 3D mesh models. The SVM learns to classify vertices as appropriate or inappropriate candidates for modification in order to accommodate the watermark. Experimental results verify that the proposed algorithm is imperceptible and robust against attacks such as mesh smoothing, cropping and noise addition.

Approximating interior bounded box of 3D character mesh model based on its skeleton and symmetry

Purpose – In the process of robot shell design, it is necessary to match the shape of the input 3D originalcharacter mesh model and robot endoskeleton, in order to make the input model fit for robot and avoidcollision. So, the purpose of this paper is to find an object of reference, which can be used for the process ofshape matching.Design/methodology/approach – In this work, the authors propose an interior bounded box (IBB)approach that derives from oriented bounding box (OBB). This kind of box is inside the closed mesh model.At the same time, it has maximum volume which is aligned with the object axis but is enclosed by all the meshvertices. Based on the IBB of input mesh model and the OBB of robot endoskeleton, the authors can completethe process of shape matching. In this paper, the authors use an evolutionary algorithm, covariance matrixadaptation evolution strategy (CMA-ES), to approximate the IBB based on skeleton and symmetry of inputcharacter mesh model.Findings – Based on the evolutionary algorithm CMA-ES, the optimal position and scale informationof IBB can be found. The authors can obtain satisfactory IBB result after this optimization process.The output IBB has maximum volume and is enveloped by the input character mesh model as well.Originality/value – To the best knowledge of the authors, the IBB is first proposed and used in the field ofrobot shell design. Taking advantage of the IBB, people can quickly obtain a shell model that fit for robot.At the same time, it can avoid collision between shell model and the robot endoskeleton.