Superquadric Modeling Method of 3D Object Based on Invasive Weeds Optimization and Levenberg-Marquardt Algorithms

Because of the problem of insufficient parameter fitting accuracy of superquadric modeling method based on Levenberg-Marquardt (LM) algorithm, a superquadric modeling method of 3D object based on invasive weed optimization (IWO) algorithm and LM algorithm is proposed. First, according to the distance relationship between each point in point cloud and the superquadric, a nonlinear optimization model for superquadric parameter estimation of 3D object is established. Then, to obtain the initial values of superquadric fitting parameters, the IWO algorithm is adopted to optimize the optimization model. After that, LM algorithm is also adopted to optimize the optimization model, and estimation values of superquadric fitting parameters of 3D object can be obtained. Thus, the superquadric model of 3D object of the given point cloud can be established. The experimental results show that the proposed method can yield highly accurate superquadric fitting parameters, and can effectively suppress the influence of measurement noise on modeling accuracy as well.