Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Uncertainty to Visual Exploration
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Autonomous Exploration: Driven by Uncertainty
IEEE Transactions on Pattern Analysis and Machine Intelligence
Superquadrics for Segmenting and Modeling Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Darboux Frames, Snakes, and Super-Quadrics: Geometry from the Bottom Up
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting Undeformed Superquadrics to Range Data: Improving Model Recovery and Classification
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Global and local deformations of solid primitives
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
A Recursive Fitting-and-Splitting Algorithm for 3-D Object Modeling Using Superquadrics
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
3-D Object Representation from Multi-View Range Data Applying Deformable Superquadrics
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Robust fitting of 3D objects by affinely transformed superellipsoids using normalization
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Genetic algorithms for 3D reconstruction with supershapes
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A robust evolutionary algorithm for the recovery of rational Gielis curves
Pattern Recognition
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Most superquadric-based three-dimensional (3D) image representation methods recover superquadric models by minimizing an appropriately defined objective function. The objective function serves as an error metric to evaluate how accurately the recovered model fits the data. Both the accuracy of the recovered superquadric model and the efficiency of the data fitting process heavily depend on the objective function used. In this paper, an experimental comparison of two primarily used objective functions in superquadric model recovery is presented. The first objective function is based on the implicit definition of superquadrics, and the other on radial Euclidean distance. A variety of synthetic and real 3D range data of both regular and globally deformed superquadrics are used in experiments. The two objective functions are compared with respect to the accuracy of the recovered parameters, corresponding fitting errors, robustness against noise, sensitivity to viewpoints, and the convergence speed. The conclusion derived in this paper provides a convincing guidance for selecting the optimal objective function in superquadric representation tasks.