{'fraction_non_alphanumeric': 0.01955104996379435, 'fraction_numerical': 0.002896451846488052, 'mean_word_length': 5.06140350877193, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Gaze guided object recognition using a head-mounted eye tracker

Wearable eye trackers open up a large number of opportunities to cater for the information needs of users in today's dynamic society. Users no longer have to sit in front of a traditional desk-mounted eye tracker to benefit from the direct feedback given by the eye tracker about users' interest. Instead, eye tracking can be used as a ubiquitous interface in a real-world environment to provide users with supporting information that they need. This paper presents a novel application of intelligent interaction with the environment by combining eye tracking technology with real-time object recognition. In this context we present i) algorithms for guiding object recognition by using fixation points ii) algorithms for generating evidence of users' gaze on particular objects iii) building a next generation museum guide called Museum Guide 2.0 as a prototype application of gaze-based information provision in a real-world environment. We performed several experiments to evaluate our gaze-based object recognition methods. Furthermore, we conducted a user study in the context of Museum Guide 2.0 to evaluate the usability of the new gaze-based interface for information provision. These results show that an enormous amount of potential exists for using a wearable eye tracker as a human-environment interface.