Abstract:
In this paper we present a novel technique for rapidly partitioning surfaces in range images into planar patches. Essential for our segmentation method is the observation that, in a scan line, the points belonging to a planar surface form a straight line segment. On the other hand, all points on a straight line segment surely belong to the same planar surface. Based on this observation, we first divide each scan line into straight line segments and subsequently consider only the set of line segments of all scan lines as segmentation primitives. We have developed a simple link-based data structure to efficiently represent line segments and their neighborhood relationship. The principle of our segmentation method is region growing. Three neighboring line segments satisfying an optimality criterion are selected as a seed region, and then a growing is carried out around the seed region. We use a noise variance estimation to automatically set some thresholds so that the algorithm can adapt ...
Citations
|
3011
|
Pattern Classification and Scene Analysis
– Duda, Hart
- 1973
|
|
120
|
Active optical range imaging sensors
– Besl
|
|
84
|
perspective on Range Finding Techniques for Computer Vision
– Jarvis, “A
- 1983
|
|
72
|
Robust clustering with applications in computer vision
– Jolion, Meer, et al.
- 1991
|
|
70
|
Segmentation of plane curves
– Pavlidis, Horowitz
- 1974
|
|
57
|
Range image understanding
– Besl, Jain
- 1985
|
|
55
|
A RANSAC-based approach to model fitting and its application to finding cylinders in range data
– Bolles, Fischler
- 1981
|
|
37
|
Optimum uniform piecewise linear approximation of planar curves
– Dunham
- 1986
|
|
22
|
Fast and robust range data acquisition in a low-cost environment
– Stahs, Wahl
- 1990
|
|
18
|
Three-dimensional vision structure for robot applications
– Nitzan
- 1988
|
|
16
|
Picture segmentation by a directed split and merge procedure," inComputer Methods in Image Analysis
– Pavlidis, Horowitz
- 1977
|
|
16
|
Fast Segmentation of Range Imagery Into Planar Regions
– Taylor, Savini, et al.
- 1989
|
|
14
|
Segmentation of range images into planar surfaces by split and merge
– Parvin, Medioni
- 1986
|
|
9
|
Fast segmentation of range images into planar regions
– Schmitt, Chen
- 1991
|
|
8
|
On Computation of the Running Median
– Astola, Campbell
- 1989
|
|
8
|
Segmentation of pictures and maps through functional approximation
– Pavlidis
- 1972
|
|
6
|
Digital Image Processing, second edition
– Pratt
- 1991
|
|
6
|
Determination of the identity, position and orientation of the topmost object in a pile
– Yang, Kak
- 1986
|
|
4
|
A comparison of splitting methods for the identification of corner points
– Espelid, Jonassen
- 1991
|
|
4
|
Finding cylinders in range data
– Lozano-Perez, Grimson, et al.
- 1987
|
|
2
|
Identification of cornerpoints of two-dimensional images using linear search
– Han, Jang, et al.
- 1989
|
|
2
|
Volumetric description of solids of revolution in a range image
– Yokoya, Levine
- 1990
|
|
1
|
Fast corner detection using linear search
– Chien
- 1991
|
|
1
|
Clustering analysis, in Digital pattern recognition
– Diday, Simon
- 1976
|
|
1
|
Noise analysis and filtering of range images produced by a scanning laser range finder
– Harkonen, Ailisto, et al.
- 1989
|
|
1
|
Fuzzy algorithms to find linear and planar clusters and their applications
– Krishnapuram, Freg
- 1991
|
|
1
|
Range image segmantion based on function approximation
– itre, Hugli, et al.
- 1990
|
|
1
|
finding on a 3 \Theta 3 grid, in Graphics Gems
– Paeth, Median
- 1990
|
|
1
|
Image compression using polylines
– Pham, Abdollahi
- 1988
|
|
1
|
Finding cones from multi-scan range images
– Shao, Volz
- 1991
|
