| dc.date.accessioned | 2004-10-04T14:24:11Z | |
| dc.date.accessioned | 2018-11-24T10:11:17Z | |
| dc.date.available | 2004-10-04T14:24:11Z | |
| dc.date.available | 2018-11-24T10:11:17Z | |
| dc.date.issued | 1992-02-01 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/5960 | |
| dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/5960 | |
| dc.description.abstract | 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. | en_US |
| dc.format.extent | 23 p. | en_US |
| dc.format.extent | 2278295 bytes | |
| dc.format.extent | 1790124 bytes | |
| dc.language.iso | en_US | |
| dc.subject | object recognition | en_US |
| dc.subject | indexing | en_US |
| dc.subject | invariants | en_US |
| dc.subject | non-accidentalsproperties | en_US |
| dc.subject | hashing | en_US |
| dc.subject | space efficiency | en_US |
| dc.title | Space Efficient 3D Model Indexing | en_US |
