Name
Abstract | ||
|---|---|---|
In this paper a novel implementation of the saliency map model on a multi-GPU platform using CUDA technology is presented. The saliency map model is a well-known computational model for bottom-up attention selection and serves as a basis of many attention control strategies of cognitive vision systems. A real-time implementation is the prerequisite of an application of bottom-up attention on mobile robots and vehicles. Parallel computation on Graphics Processing Unit (GPU) provides an excellent solution for this kind of compute-intensive image processing. Running on 1 to 4 NVIDIA GeForce 8800 (GTX) graphics cards a frame rate of 313 fps at resolution of 640 × 480 is achieved, which is approximately 8.5 times faster than the standard implementations on CPUs. The implementation is also evaluated using a high-speed camera at 200 Hz. Using two GPUs only 2 ms extra computational time for the saliency map generation in addition to the camera capture time is required for images of 640 × 480 pixels. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ROBOT.2009.5152357 | ICRA |
Keywords | Field | DocType |
bottom-up attention selection,well-known computational model,standard implementation,bottom-up attention,saliency map generation,novel implementation,camera capture time,real-time implementation,attention control strategy,saliency map model,high-speed multi-gpu implementation,concurrent computing,pixel,bottom up,computational modeling,mobile robot,image processing,parallel computation,image resolution,convolution,computer model,graphics,visualization,mobile robots,multi threading,computer vision,parallel computer,machine vision,kernel,attentional control | Graphics,Machine vision,Computer graphics (images),Computer science,CUDA,Image processing,General-purpose computing on graphics processing units,Frame rate,Graphics processing unit,Image resolution | Conference |
Volume | Issue | ISSN |
2009 | 1 | 1050-4729 |
Citations | PageRank | References |
14 | 0.91 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tingting Xu | 1 | 123 | 9.59 |
| Thomas Pototschnig | 2 | 18 | 1.79 |
| Kolja Kühnlenz | 3 | 430 | 40.87 |
| Martin Buss | 4 | 1799 | 159.02 |