Multiscale Keypoint Analysis based on Complex Wavelets
Pashmina Bendale, William Triggs and Nick Kingsbury
In: British Machine Vision Conference, 31 Aug - 3 Sep 2010, Aberystwyth, U.K..
We describe a new multiscale keypoint detector and a set of local visual
descriptors, both based on the efficient Dual-Tree Complex Wavelet Transform.
The detector has properties and performance similar to multiscale
Foerstner-Harris detectors. The descriptor provides efficient rotation-invariant
matching. We evaluate the method, comparing it to a previous wavelet based
approach and to several conventional detectors and descriptors on a new
dataset designed for the automatic evaluation of 3D viewpoint invariance. The
dataset contains over 4000 images of toy cars on a turntable under accurately
calibrated conditions. Both it and the evaluation software are publicly available. Overall
the method gives performance competitive with existing Harris-like detectors.
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||William Triggs|
|Deposited On:||07 March 2011|