Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast segmentation of range imagery into planar regions
Computer Vision, Graphics, and Image Processing
Three-dimensional alpha shapes
ACM Transactions on Graphics (TOG)
Segmentation of range images as the search for geometric parametric models
International Journal of Computer Vision
Direct construction of polynomial surfaces from dense range images through region growing
ACM Transactions on Graphics (TOG)
Superquadrics for Segmenting and Modeling Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Edges and Lines in Images
Finding Edges and Lines in Images
Surface mesh segmentation and smooth surface extraction through region growing
Computer Aided Geometric Design
Fitting B-spline curves to point clouds by curvature-based squared distance minimization
ACM Transactions on Graphics (TOG)
Surface mesh segmentation and smooth surface extraction through region growing
Computer Aided Geometric Design
GMP'06 Proceedings of the 4th international conference on Geometric Modeling and Processing
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A segmentation and model-reconstruction algorithm is proposed based on polynomial approximation and on a novel version of "region growing". First, an initial partition is calculated on the basis of differential-geometric properties of the range image. Then, the first merging procedure is applied ("merge with constraints") aiming at correctly identifying principal surfaces of the model. It examines all possible mergers of regions and selects those satisfying strict compatibility constraints. The second merging procedure relaxes these constraints to produce the final segmentation. Theoretical work is presented proving the consistency of these merging procedures. Finally, application of the algorithm on industrial data is presented demonstrating the efficiency of the proposed methodology.