| dc.creator |
Jacobs, David W. |
|
| dc.date |
2004-10-04T14:24:11Z |
|
| dc.date |
2004-10-04T14:24:11Z |
|
| dc.date |
1992-02-01 |
|
| dc.date.accessioned |
2013-10-09T02:42:07Z |
|
| dc.date.available |
2013-10-09T02:42:07Z |
|
| dc.date.issued |
2013-10-09 |
|
| dc.identifier |
AIM-1353 |
|
| dc.identifier |
http://hdl.handle.net/1721.1/5960 |
|
| dc.identifier.uri |
http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
|
| dc.description |
We show that we can optimally represent the set of 2D images produced by the point features of a rigid 3D model as two lines in two high-dimensional spaces. We then decribe a working recognition system in which we represent these spaces discretely in a hash table. We can access this table at run time to find all the groups of model features that could match a group of image features, accounting for the effects of sensing error. We also use this representation of a model's images to demonstrate significant new limitations of two other approaches to recognition: invariants, and non- accidental properties. |
|
| dc.format |
23 p. |
|
| dc.format |
2278295 bytes |
|
| dc.format |
1790124 bytes |
|
| dc.format |
application/postscript |
|
| dc.format |
application/pdf |
|
| dc.language |
en_US |
|
| dc.relation |
AIM-1353 |
|
| dc.subject |
object recognition |
|
| dc.subject |
indexing |
|
| dc.subject |
invariants |
|
| dc.subject |
non-accidentalsproperties |
|
| dc.subject |
hashing |
|
| dc.subject |
space efficiency |
|
| dc.title |
Space Efficient 3D Model Indexing |
|