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Geometric Snakes for Triangular Meshes
Author(s) -
Lee Y.,
Lee S.
Publication year - 2002
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/1467-8659.t01-1-00582
Subject(s) - morphing , polygon mesh , computer science , feature (linguistics) , computer vision , artificial intelligence , geometric modeling , triangle mesh , t vertices , mesh generation , position (finance) , collision detection , image processing , computer graphics (images) , image (mathematics) , geometry , mathematics , collision , physics , finite element method , thermodynamics , philosophy , linguistics , computer security , finance , economics
Feature detection is important in various mesh processing techniques, such as mesh editing, mesh morphing, mesh compression, and mesh signal processing. In spite of much research in computer vision, automatic feature detection even for images still remains a difficult problem. To avoid this difficulty, semi‐automatic or interactive techniques for image feature detection have been investigated. In this paper, we propose a geometric snake as an interactive tool for feature detection on a 3D triangular mesh. A geometric snake is an extension of an image snake, which is an active contour model that slithers from its initial position specified by the user to a nearby feature while minimizing an energy functional. To constrain the movement of a geometric snake onto the surface of a mesh, we use the parameterization of the surrounding region of a geometric snake. Although the definition of a feature may vary among applications, we use the normal changes of faces to detect features on a mesh. Experimental results demonstrate that geometric snakes can successfully capture nearby features from user‐specified initial positions.