Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Gaze is frequently explored in public display research given its importance for monitoring and analysing audience attention. Hover, current gaze-enabled public display interfaces require either special-purpose eye tracking equipment or explicit personal calibration for each individual user.  present  AggreGaze , a novel method for estimating spatio-temporal audience attention on public displays. Our method requires only a single off-the-shelf camera attached to the display, does not require any personal calibration, and provides visual attention estimates across the full display.  achieve this by 1) compensating for errors of state-of-the-art appearance-based gaze estimation methods through on-site training data collection, and by 2) aggregating uncalibrated and thus inaccurate gaze estimates of multiple users into joint attention estimates.  propose different visual stimuli for this compensation: a standard 9-point calibration, moving targets, text and visual stimuli embedded into the display content, as ll as normal video content. Based on a two-ek deployment in a public space,  demonstrate the effectiveness of our method for estimating attention maps that closely resemble ground-truth audience gaze distributions.
['Yusuke Sugano', 'Xucong Zhang', 'Andreas Bulling']
I am writing a research paper on a idea AggreGaze: Collective Estimation of Audience Attention on Public Displays
[{"from": "human", "value": "I am writing a research paper on a idea AggreGaze: Collective Estimation of Audience Attention on Public Displays"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Gaze is frequently explored in public display research given its importance for monitoring and analysing audience attention. Hover, current gaze-enabled public display interfaces require either special-purpose eye tracking equipment or explicit personal calibration for each individual user.  present  AggreGaze , a novel method for estimating spatio-temporal audience attention on public displays. Our method requires only a single off-the-shelf camera attached to the display, does not require any personal calibration, and provides visual attention estimates across the full display.  achieve this by 1) compensating for errors of state-of-the-art appearance-based gaze estimation methods through on-site training data collection, and by 2) aggregating uncalibrated and thus inaccurate gaze estimates of multiple users into joint attention estimates.  propose different visual stimuli for this compensation: a standard 9-point calibration, moving targets, text and visual stimuli embedded into the display content, as ll as normal video content. Based on a two-ek deployment in a public space,  demonstrate the effectiveness of our method for estimating attention maps that closely resemble ground-truth audience gaze distributions."}]