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| 2016-08-04 09:51:12 -0600 | received badge | ● Student (source) |
| 2014-08-01 16:23:51 -0600 | asked a question | SURG_GPU masking Hello all, I'm using SURF_GPU to find features on a large (40 MPx) image. On Quatro K2000 with 2 GB of GPU RAM, it fails due to 'insufficient memory' I thought that using mask should reduce memory footprint, but it did not help. GPU memory consumption looks independent of mask size. Does anybody here have experience processing large images on GPU? What would be the best approach when performance is important? Actually I need to process even larger images - upto several hundred MPx Thank you |
| 2014-07-30 09:57:04 -0600 | commented question | SURF performance Thank you very much. I thought OpenCV optimizes pipelining itself. Now I will do it. Thanks |
| 2014-07-29 08:50:03 -0600 | commented question | SURF performance My input data is ~6k x 7k pixels (40MPx) The same (no difference in performance) even for 512 x 512 image |
| 2014-07-28 15:22:45 -0600 | asked a question | SURF performance Hello, I'm using SurfFeatureDetector along with SurfDescriptorExtractor and FlannBasedMatcherto align images. I tried to replace SurfFeatureDetector with gpu::SURF_GPU I was expecting performance improvements, but the processing time stays almost same (within 5%) My GPU is Quadro K2000 2GB and CPU is Xeon E5-1650 v2 @3.5GHz I have same situation (almost no improvement in speed) in Remap and gpu::Remap I'm not counting first run of GPU function in timing Is there a way to make GPU processing faster? I'm using OpenCV 2.4.9 compiled with VS2012 and CUDA 6.0 |