Name
Abstract | ||
|---|---|---|
The Signature Quadratic Form Distance on feature signatures represents a flexible distance-based similarity model for effective content-based multimedia retrieval. Although metric indexing approaches are able to speed up query processing by two orders of magnitude, their applicability to large-scale multimedia databases containing billions of images is still a challenging issue. In this paper, we propose the utilization of GPUs for efficient query processing with the Signature Quadratic Form Distance. We show how to process multiple distance computations in parallel and demonstrate efficient query processing by comparing many-core GPU with multi-core CPU implementations. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2063576.2063970 | CIKM |
Keywords | Field | DocType |
challenging issue,efficient query processing,effective content-based multimedia retrieval,large-scale multimedia databases,many-core gpu,signature quadratic form distance,flexible distance-based similarity model,query processing,many-core gpu architecture,feature signature,metric indexing approach,indexation,similarity search,quadratic form | Query optimization,Data mining,Information retrieval,Query expansion,Computer science,Quadratic form,Search engine indexing,Order of magnitude,Nearest neighbor search,Speedup,Computation | Conference |
Citations | PageRank | References |
8 | 0.53 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Krulis | 1 | 76 | 13.27 |
| Jakub Lokoč | 2 | 135 | 10.82 |
| Christian Beecks | 3 | 431 | 39.14 |
| Tomáš Skopal | 4 | 393 | 29.84 |
| Thomas Seidl | 5 | 3515 | 544.45 |