Efficient generation of discontinuity-preserving adaptive triangulations from range images

This paper presents an efficient technique for generating adaptive triangular meshes from range images. The algorithm consists of two stages. First, a user-defined number of points is adaptively sampled from the given range image. Those points are chosen by taking into account the surface shapes rep...

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Bibliographic Details
Published in:IEEE transactions on cybernetics 2004-10, Vol.34 (5), p.2003-2014
Main Authors: Garcia, M.A., Sappa, A.D.
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Artificial Intelligence
Computer vision
Curvature
Cybernetics
Discontinuity
Gain
Image Interpretation, Computer-Assisted - methods
Image segmentation
Image sensors
Imaging, Three-Dimensional - methods
Intelligent robots
Mathematical analysis
Parallel algorithms
Pattern Recognition, Automated
Photogrammetry - methods
Pixel
Robot sensing systems
Robot vision systems
Shape
Studies
Two dimensional displays
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Summary:This paper presents an efficient technique for generating adaptive triangular meshes from range images. The algorithm consists of two stages. First, a user-defined number of points is adaptively sampled from the given range image. Those points are chosen by taking into account the surface shapes represented in the range image in such a way that points tend to group in areas of high curvature and to disperse in low-variation regions. This selection process is done through a noniterative, inherently parallel algorithm in order to gain efficiency. Once the image has been subsampled, the second stage applies a two and one half-dimensional Delaunay triangulation to obtain an initial triangular mesh. To favor the preservation of surface and orientation discontinuities (jump and crease edges) present in the original range image, the aforementioned triangular mesh is iteratively modified by applying an efficient edge flipping technique. Results with real range images show accurate triangular approximations of the given range images with low processing times.
ISSN:1083-4419
2168-2267
1941-0492
2168-2275
DOI:10.1109/TSMCB.2004.832156