1. An eye tracking system comprising: a video capture component configured to provide a video of an environment and a set of gaze tracking coordinates representing, for each of a plurality of frames comprising the video, a position within the environment at which a user is looking; a library, configured to store a plurality of feature sets representing respective areas of interest, with each area of interest including an object label representing an object of interest within the environment; an image annotation component configured to extract a plurality of features from a region of interest, defined around the gaze coordinates for a given frame, and match the extracted features to an area of interest in the library to produce a selected area of interest and a confidence value; and a verification component configured to accept the selected area of interest if the confidence value meets a threshold value and send the region of interest to a human expert at a user interface to assign an object label to the region of interest if the confidence value does not meet the threshold value; wherein 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.
1. An eye tracking system comprising: a video capture component configured to provide a video of an environment and a set of gaze tracking coordinates representing, for each of a plurality of frames comprising the video, a position within the environment at which a user is looking; a library, configured to store a plurality of feature sets representing respective areas of interest, with each area of interest including an object label representing an object of interest within the environment; an image annotation component configured to extract a plurality of features from a region of interest, defined around the gaze coordinates for a given frame, and match the extracted features to an area of interest in the library to produce a selected area of interest and a confidence value; and a verification component configured to accept the selected area of interest if the confidence value meets a threshold value and send the region of interest to a human expert at a user interface to assign an object label to the region of interest if the confidence value does not meet the threshold value; wherein 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. 3. The eye tracking system of claim 1 , wherein the set of features extracted from the region of interest comprises a plurality of features extracted via a spatial pyramid histogram technique.