BMVC 2004, Kingston, 7th-9th Sept, 2004
Learning to detect low-level features
P. Hall and M. Owen (University of Bath)
We introduce a method to detect low-level features that is prescriptive (as
Canny edge-detection is) but trained by a user. The user simply chooses feature
classes and points to class instances. Given a input image, we compute
a probability map that indicates how likely it is to belong to each of the userdefined
classes; so combining different kinds of feature detector into a single,
user-trainable system. This paper explains how we characterise features, how
we train and detect, and gives an algorithm that automatically determines feature
scale. We empirically compare the method to standard edge and corner
detectors, showing a measurable advantage in each case.
(pdf article)