Name
Abstract | ||
|---|---|---|
The eccentricity transform associates to each point of a shape the distance to the point farthest away from it. The transform is defined in any dimension, for open and closed manyfolds, is robust to Salt & Pepper noise, and is quasi-invariant to articulated motion. This paper presents and algorithm to efficiently compute the eccentricity transform of a polygonal shape with or without holes. In particular, based on existing and new properties, we provide an algorithm to decompose a polygon using parallel steps, and use the result to derive the eccentricity value of any point. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76725-1_31 | CIARP |
Keywords | Field | DocType |
eccentricity value,closed manyfolds,new property,articulated motion,pepper noise,parallel step,paper present,polygonal shape,distance transform,polygon | Computer vision,Polygon,Eccentricity (behavior),Computer science,Distance transform,Artificial intelligence | Conference |
Volume | ISSN | ISBN |
4756 | 0302-9743 | 3-540-76724-X |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Walter G. Kropatsch | 1 | 896 | 152.91 |
| Adrian Ion | 2 | 222 | 21.11 |
| Samuel Peltier | 3 | 77 | 10.05 |