Summary15
From EQUIS Lab Wiki
When viewing an image, users tend to distribute their eye gaze in a manner that reveals the relevance of the presented information.
Knowledge about the user’s looking behavior may be applied in 1. Information Filtering. Information on a display can be filtered on the basis of user fixations at an area, with unattended areas being abstracted or removed Such displays are known as Gaze-contingent displays, and have been deployed to optimize graphics rendering capacity 2. Dynamic Interaction. Areas that attract user attention can be used to trigger specific sound, motion, or other meaningful responses Displays can ensure information is visible by presenting it within field of view.
the paper deals with 50' plasma screen capable of tracking user eye movements from a distance, and without calibration.
Painters have been long known to use lighting and detail to guide the eyes of observers to significant areas of the artwork. By doing so, the artist aims to reduce the scene to its most essential elements, thus lowering cognitive demand while aiding comprehension of the image In Attentive Art, this process is made interactive. By responding to user attention, attentive artworks become a form of Attentive User Interface (AUI).
Displayed an image of a painting on a large eyetracking display, tracked where the users fixated on the display. Based on statistics gathered, illuminated the areas that people fixated on. The process alters the image, guiding and influencing subsequent users perception.
technical - about the monitor and displays
CONCLUSION We presented ECS Display, a large screen that tracks the user’s point of gaze from a distance without any calibration. We discussed how we applied ECS Display in the design of Attentive Art. Artworks displayed on the ECS Display respond directly to user interest by visually highlighting areas of the artwork that receive attention, and by darkening areas that receive little interest. This results in an increasingly abstract artwork that provides guidance to subsequent viewers. We believe the dynamical filtering of information on the basis of user interest allows cognitive load associated with large display visualizations to be managed more effectively.
