Eye Tracking as Interface for the Design of Generative Visual Forms and Patterns

When working with generative systems, designers enter into a loop of discrete steps; external evaluations of the output feedback into the system, and new outputs are subsequently reevaluated. In such systems, interacting low level elements can engender a difficult to predict emergence of macro-level characteristics. Furthermore, the state space of some systems can be vast. Consequently, designers generally rely on trial-and-error, experience or intuition in selecting parameter values to develop the aesthetic aspects of their de- signs. We investigate an alternative means of exploring the state spaces of generative visual systems by using a gaze- contingent display. A user's gaze continuously controls and directs an evolution of visual forms and patterns on screen. As time progresses and the viewer and system remain coupled in this evolution, a population of generative artefacts tends towards an area of their state space that is 'of interest', as defined by the eye tracking data. The evaluation-feedback loop is continuous and uninterrupted, gaze the guiding feedback mechanism in the exploration of state space. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

The 'H' in HCI: enhancing perception of the interactive through the performative.

Motion sensing technologies are well developed at the bio-mechanical (motion capture) and geo-locative (GPS) scales. However, there are many degrees of scale between these extremes and there have been few attempts to seek the integration of systems that were designed for distinct contexts and tasks. The proposition that motivated the Scale project team was that through such systems integration it would be possible to create an enhanced perception of interaction between human participants who might be co-located or remotely engaged, separated in either (or both) time or space. A further aim was to examine how the use of these technologies might inform current s discourse on the performative

Cognitive music modelling: An information dynamics approach

Abstract—We describe an information-theoretic approach to the analysis of music and other sequential data, which emphasises the predictive aspects of perception, and the dynamic process of forming and modifying expectations about an unfolding stream of data, characterising these using the tools of information theory: entropies, mutual informations, and related quantities. After reviewing the theoretical foundations, we discuss a few emerging areas of application, including musicological analysis, real-time beat-tracking analysis, and the generation of musical materials as a cognitively-informed compositional aid. I