Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Recovery of Piled Deformable Objects Using Superquadrics
Proceedings of the 24th DAGM Symposium on Pattern Recognition
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
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In this paper, a new algorithm IPPSO (Parallel Particle Swarm Optimization with Island model) is proposed. It aims at remedying the defect of superquadric parametric fitting problem which is solved with L-M (Levenberg- Marquardt) method in 3D reconstruction and improving the algorithm performance of particle swarm optimization for application to large-scale problems and multi-variable solutions. This paper investigates 3D representation characteristics of superquadrics and makes analysis for the defect of superquadric parametric model fitting by L-M algorithm. It presents the principle and the implementation of superquadric parametric model fitting by using IPPSO. In addition, it describes the design principle and implementation method of IPPSO. In the end, the simulation results are analyzed. The results show the good effectiveness of the proposed approach, especially in the accuracy and discernment of superquadric 3D models reconstruction for objects.