DocumentCode
2458207
Title
Contour Grouping Based on Local Symmetry
Author
Adluru, Nagesh ; Latecki, Longin Jan ; Lakaemper, Rolf ; Young, Thomas ; Bai, Xiang ; Gross, Ari
Author_Institution
Temple Univ., Philadelphia
fYear
2007
fDate
14-21 Oct. 2007
Firstpage
1
Lastpage
8
Abstract
The paper deals with grouping of edges to contours of shapes using only local symmetry and continuity. Shape skeletons are used to generate the search space for a version of the Markov Chain Monte Carlo approach utilizing particle filters to find the most likely skeleton. Intuitively this means that grouping of edge segments is performed by walking along the skeleton. The particle search, which is an adapted version of a successful algorithm in robot mapping, is assisted by a reference model of a shape, which is expressed as the sequence of sample points and radii of maximal skeleton disks. This model is sufficiently flexible to represent non-rigid deformations, but restrictive enough to perform well on real, noisy image data. The order of skeleton points (and their corresponding segments) found by the particles defines the grouping.
Keywords
Markov processes; Monte Carlo methods; SLAM (robots); edge detection; particle filtering (numerical methods); search problems; Markov chain Monte Carlo approach; contour grouping; maximal skeleton disks; nonrigid deformations; particle filters; robot mapping; search space; shape skeletons; Educational institutions; Image segmentation; Legged locomotion; Monte Carlo methods; Noise shaping; Particle filters; Robots; Shape; Simultaneous localization and mapping; Skeleton;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location
Rio de Janeiro
ISSN
1550-5499
Print_ISBN
978-1-4244-1630-1
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2007.4408879
Filename
4408879
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