Abstract: Systems and methods for eye tracking include a video capture component that provides a video of an environment and a set of gaze tracking coordinates for the video. A library stores a plurality of feature sets representing respective areas of interest with respective object labels. An image annotation component extracts a plurality of features from a region of interest and matches the extracted features to an area of interest in the library to produce a selected area of interest and a confidence value. A verification component accepts the selected area of interest if the confidence value meets a threshold value and sends the region of interest to a human expert to assign an object label if the confidence value does not. The library is dynamically updated in response to input from the human expert to add new areas of interest and new object labels to the library.

Abstract: Systems and methods for eye tracking include a video capture component that provides a video of an environment and a set of gaze tracking coordinates for the video. A library stores a plurality of feature sets representing respective areas of interest with respective object labels. An image annotation component extracts a plurality of features from a region of interest and matches the extracted features to an area of interest in the library to produce a selected area of interest and a confidence value. A verification component accepts the selected area of interest if the confidence value meets a threshold value and sends the region of interest to a human expert to assign an object label if the confidence value does not. The library is dynamically updated in response to input from the human expert to add new areas of interest and new object labels to the library.