Detail of Publication
| Text Language | English |
|---|---|
| Authors | Masakazu Iwamura, Tomohiro Nakai, and Koichi Kise |
| Title | Improvement of Retrieval Speed and Required Amount of Memory for Geometric Hashing by Combining Local Invariants |
| Journal | Proc. 18th British Machine Vision Conference (BMVC2007) |
| Vol. | 2 |
| Pages | pp.1010-1019 |
| Location | Warwick, UK |
| Reviewed or not | Reviewed |
| Month & Year | September 2007 |
| Abstract | The geometric hashing (GH) is a well-known model-based object recognition technique with good properties both in retrieval speed and required amount of memory. However, it has a significant weak point; as the number of objects increases, both retrieval speed and required amount of memory increase in the cubic, fourth or higher order. Recently, a new technique ``locally likely arrangement hashing (LLAH)'' whose computational cost is a linear order has been proposed. The objective of the current paper is to reveal how LLAH improves the performance. By comparing GH and LLAH, we describe four primary factors of the performance improvement. |
- Following file is available.
- Entry for BibTeX
@InProceedings{Iwamura2007, author = {Masakazu Iwamura and Tomohiro Nakai and Koichi Kise}, title = {Improvement of Retrieval Speed and Required Amount of Memory for Geometric Hashing by Combining Local Invariants}, booktitle = {Proc. 18th British Machine Vision Conference (BMVC2007)}, year = 2007, month = sep, volume = {2}, pages = {1010--1019}, location = {Warwick, UK} }