I am trying to find an objects position with opencv and sift, but the object I try to detect doesn't have any good reliable features. So I thought about sticking something to the object. (Some sort of pattern, like a QR code or so, not an image of another object.)
Is there a good pattern with a lot of sift features which delivers reliable data for object recognition?
You mention two different problems:
One approach to tackle the first problem (in your context) that is suited for local features is to attach custom markers to the object that yield the maximum response of the corresponding feature detector. See the following publication for a solution: F. Schweiger, B. Zeisl, P. Georgel, G. Schroth, E. Steinbach, N. Navab, Maximum Detector Response Markers for SIFT and SURF, Vision, Modeling and Visualization Workshop (VMV), Braunschweig, November 2009.
The latter problem is more fuzzy but the authors of above publication also provide a way to encode a signature in related manner.
Since the SIFT operator actually searches for regions with high change in gradient information (simply put - a Harris Corner approach) you will need a pattern with much information. Binary patterns are mostly not that interesting to find a lot of SIFT features.
I would suggest to use something with alot of clutter, like this example:
Asked: 2013-05-08 03:00:11 -0600
Seen: 607 times
Last updated: May 11 '13
