Name
Abstract | ||
|---|---|---|
Fast corner-detector algorithms are important for achieving real time in different computer vision applications. In this paper, we present new algo- rithm implementations for corner detection that make use of graphics pro- cessing units (GPU) provided by commodity hardware. The programmable capabilities of modern GPUs allow speeding up counterpart CPU algorithms. In the case of corner-detector algorithms, most steps are easily translated from CPU to GPU. However, there are challenges for mapping the feature selection step to the GPU parallel computational model. This paper presents a template for implementing corner-detector algorithms that run entirely on GPU, resulting in significant speed-ups. The proposed template is used to implement the KLT corner detector and the Harris corner detector, and nu- merical results are presented to demonstrate the algorithms efficiency. |
Year | Venue | Keywords |
|---|---|---|
2008 | BMVC | feature selection,real time,computer vision,parallel computer,corner detection |
Field | DocType | Citations |
Graphics,Computer graphics (images),Corner detection,Feature selection,Computer science,Algorithm,Implementation,Commodity hardware,Corner detector | Conference | 10 |
PageRank | References | Authors |
0.81 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas Teixeira | 1 | 30 | 6.93 |
| Waldemar Celes Filho | 2 | 235 | 23.88 |
| Marcelo Gattass | 3 | 382 | 48.43 |