Name
Abstract | ||
|---|---|---|
This paper describes a robust regular polygon detector. Given image edges, we derive the a posteriori probability for a mixture of regular polygons, and thus the probability density function for the appearance of a set of regular polygons. Likely regular polygons can be isolated quickly by discretising and collapsing the search space into three dimensions. We derive a complete formulation for efficiently recovering the remaining dimensions using maximum likelihood at the locations of the most likely polygons. Results show robustness to noise, the ability to find and differentiate different shape types, and to perform real-time sign detection for driver assistance. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.patcog.2009.09.008 | Pattern Recognition |
Keywords | Field | DocType |
posteriori probability,likely regular polygon,shape detection,regular polygon detection,probability density function,regular polygon,likely polygon,image edge,driver assistance,robust regular polygon detector,differentiate different shape type,sign recognition,complete formulation,search space,maximum likelihood,real time,three dimensions,computer and information science | Polygon,Combinatorics,Rectilinear polygon,Polygon mesh,Polygon (computer graphics),Algorithm,Smoothing group,Regular polygon,Point in polygon,Star-shaped polygon,Mathematics | Journal |
Volume | Issue | ISSN |
43 | 3 | Pattern Recognition |
Citations | PageRank | References |
11 | 0.58 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nick Barnes | 1 | 577 | 68.68 |
| Gareth Loy | 2 | 627 | 42.88 |
| David Shaw | 3 | 11 | 0.58 |