Multivariate statistical methods: a primer
Multivariate statistical methods: a primer
Constraints on deformable models: recovering 3D shape and nongrid motion
Artificial Intelligence
Unsupervised Optimal Fuzzy Clustering
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
Geometrically deformed models: a method for extracting closed geometric models form volume data
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Dynamic deformation of solid primitives with constraints
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constructing Intrinsic Parameters with Active Models for Invariant Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection and Separation of Ring-Shaped Clusters Using Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Global and local deformations of solid primitives
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Superquadrics and Angle-Preserving Transformations
IEEE Computer Graphics and Applications
Generic fitted shapes (GFS): Volumetric object segmentation in service robotics
Robotics and Autonomous Systems
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This paper develops a sophisticated approach to a method for fitting of complex 3-D shapes to unsegmented sets of data. The approach features dynamic models consisting of parametrically defined solid primitives (such as superquadrics), global geometric transformations, global deformations and local finite element deformations. Our technique deals with a deformable model consisting of multiple primitives (parts) that can be used to represent even more complex shapes than are common in the natural world. The deformable model is extended to the case of unsegmented data, incorporating an extended version of a fuzzy clustering technique. The image or range data are transformed into forces acting on the model that deform and conform to the given data set while continually synthesizing nonrigid motion. An adaptive procedure updates a damping factor in accordance with the largest possible step in an implemented iteration process. We demonstrate the fitting process in experiments involving the extraction of the shape of the mouse embryo's organs from microscopic sections.