An adaptive transparency algorithm for visual search using an eye-tracker

Abstract

Visual search is an important element of human-computer interaction. Whether one is playing games, analyzing medical images, or browsing the Web, they are performing many visual searches; they are looking for things. As computer interfaces become more complex, and eye-tracking input devices become more integrated into everyday lives, there is an increasing opportunity to develop appropriate support for efficient visual searches. Efficient visual searches are quicker, more successful, arguably less stressful, and may result in a more pleasurable interaction compared to inefficient visual searches. Considering that the number of items an average person can attend to at once is quite small, this research seeks to reduce and re-move distractors in a conjunctive visual search task by utilizing gaze-contingent, attentional, fade functions. It is demonstrated that a real-time reduction in distractors leads to an increase in search efficiency.