Human Attention Span Modeling using 2D Visualization Plots for Gaze Progression and Gaze Sustenance

Abstract

This paper presents a novel perspective on human attention span modeling based on gaze estimation from head pose data extracted from videos. This is achieved by devising specialized 2D visualization plots that capture gaze progression and gaze sustenance over time. In doing so, a low-resolution analysis is assumed, as is the case with most crowd surveillance videos wherein the retinal analysis and iris pattern extraction of individual subjects is made impossible. The information is useful for studies involving the random gaze behavior pattern of humans in a crowded place, or in a controlled environment in seminars or office meetings. The extraction of useful information regarding the attention span of the individual from the spatial and temporal analysis of gaze points is the subject of study in this paper. Different solutions ranging from plotting temporal gaze plots to sustained attention span graphs are investigated, and the results are compared with the existing techniques of attention span modeling and visualization.