PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Learning an Interest Operator from Human Eye Movements
Wolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf and Matthias Franz
In: CVPR 2006(2006).


We present an approach for designing interest operators that are based on human eye movement statistics. In contrast to existing methods which use hand-crafted saliency measures, we use machine learning methods to infer an interest operator directly from eye movement data. That way, the operator provides a measure of biologically plausible interestingness. We describe the data collection, training, and evaluation process, and show that our learned saliency measure significantly accounts for human eye movements. Furthermore, we illustrate connections to existing interest operators, and present a multi-scale interest point detector based on the learned function.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:2291
Deposited By:Wolf Kienzle
Deposited On:02 November 2006