Estimating 3-D Point-of-Regard in a Real Environment Using a Head-Mounted Eye-Tracking System

Unlike conventional portable eye-tracking methods that estimate the position of the mounted camera using 2-D image coordinates, the techniques that are proposed here present richer information about person's gaze when moving over a wide area. They also include visualizing scanpaths when the user with a head-mounted device makes natural head movements. We employ a Visual SLAM technique to estimate the head pose and extract environmental information. When the person's head moves, the proposed method obtains a 3-D point-of-regard. Furthermore, scanpaths can be appropriately overlaid on image sequences to support quantitative analysis. Additionally, a 3-D environment is employed to detect objects of focus and to visualize an attention map.