Name
Abstract | ||
|---|---|---|
In this paper we propose a new framework for view-invariant 3D object recognition, based on what we call Visibility Maps. A Visibility Map (VM) encodes a compact model of an arbitrary 3D object for which a set of images taken from different views is available. Representative local invariant features extracted from each image are selectively combined to form a visibility basis, in terms of which an arbitrary view of the modeled object can be represented. A metric which incorporates geometric information is also provided for comparing test images to the model, and can be used for recognition. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.260 | ICPR |
Keywords | DocType | Citations |
different view,object recognition,arbitrary view,new framework,visibility maps,view-invariant object recognition,test image,compact model,geometric information,representative local invariant,visibility map,image recognition,sparse matrices,mathematical model,computational modeling,feature extraction | Conference | 1 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bisser Raytchev | 1 | 212 | 33.11 |
| Tetsuya Mino | 2 | 1 | 0.34 |
| Toru Tamaki | 3 | 120 | 30.21 |
| Kazufumi Kaneda | 4 | 439 | 86.44 |