Title :
Perception-based 3D triangle mesh segmentation using fast marching watersheds
Author_Institution :
Imaging, Robotics, & Intelligent Syst. Lab., Univ. of Tennessee, Knoxville, TN, USA
Abstract :
In this paper, we describe an algorithm called fast marching watersheds that segments a triangle mesh into visual parts. This computer vision algorithm leverages a human vision theory known as the minima rule. Our implementation computes the principal curvatures and principal directions at each vertex of a mesh, and then our hill-climbing watershed algorithm identifies regions bounded by contours of negative curvature minima. These regions fit the definition of visual parts according to the minima rule. We present evaluation analysis and experimental results for the proposed algorithm.
Keywords :
computer vision; image segmentation; mesh generation; object recognition; stereo image processing; visual perception; 3D surface; 3D triangle mesh; computer vision algorithm; evaluation analysis; fast marching watersheds; hill-climbing watershed algorithm; human vision theory; mesh segmentation; mesh vertex; minima rule; negative curvature minima contour; object recognition; perception-based segmentation; principal curvature; principal direction; region identification; Algorithm design and analysis; Computer vision; Data structures; Humans; Image segmentation; Intelligent robots; Intelligent systems; Laboratories; Robustness; Surface fitting;
Conference_Titel :
Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
Print_ISBN :
0-7695-1900-8
DOI :
10.1109/CVPR.2003.1211448