The JAMF attention modelling framework

Abstract

Many models of attention have been implemented in recent years, but comparison and further development are difficult due to the lack of a common platform. We present JAMF, an open source simulation framework for drag & drop design and high-performance execution of attention models. Its building blocks are "Components", functional units encapsulating specific algorithms. Simulations are created in the graphical JAMF client by connecting Components from the server's repository. Today it contains Components suitable for replication and extension of many major models of attention. Simulations are executed on the JAMF server by translation of model definitions into binary applications, while automatically exploiting the model's structure for parallel execution. By disentangling design and algorithmic implementation, the JAMF architecture combines a novel tool for rapid test and implementation of attention models with a high-performance execution engine. © 2009 Springer Berlin Heidelberg.