A filterbank for low-level vision
At the moment I have the pleasure to be at MSRC , working under the supervision of Carsten Rother and Sebastian Nowozin . We are tackling some low-level vision tasks (as in their recent CVPR paper ) and in this context, filter banks are very useful. They might also be useful for object detection, since one Gabor rules them all , and Google uses collections of Gabor filters for his image retrieval. I used the maximum response bank from the website of Andrew Zissermans Visual Geometry group here . My Python adaption is available as a github gist . The Root Filter set looks like this: