PT Journal
AU J.S. Cope
   P.Remagnino
   S.Mannan
   Katerine Diaz
   Francesc J. Ferri
   P.Wilkin
TI Reverse Engineering Expert Visual Observations: From Fixations To The Learning Of Spatial Filters With A Neural-Gas Algorithm
SO Expert Systems with Applications
JI EXWA
PY 2013
BP 6707
EP 6712
VL 40
IS 17
DI 10.1016/j.eswa.2013.05.042
DE Neural gas; Expert vision; Eye-tracking; Fixations
AB Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give high responses to image regions which a human expert fixated on. These filters can then be used to identify regions in other images which are likely to be useful for a given vision task. The algorithm is evaluated by learning filters for locating specific areas of plant leaves.
ER