{'fraction_non_alphanumeric': 0.01296111665004985, 'fraction_numerical': 0.004985044865403789, 'mean_word_length': 5.048192771084337, '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}}
SEONSORS FOR TRACKING , TRIGGERING AND INITIAL 3 D MODELING

We propose a novel face capture system for security gateways which allows for inexpensive rapid automated or computer-aided face-based person authentication employing 3D head and face data. By face-based person authentication we refer to the process of comparing the appearance of a person to a visual representation of that person stored on a security document. This comparison can be done either manually or automatically and the data to be compared may be a standard facial image or a 3D representation of the person’s head, depending on the capabilities of the security document. We propose algorithms for 3D reconstruction of persons passing the security gate as well as for head pose estimation and compensation to enable precise alignment of the 3D representation to be compared to the document. Furthermore, we show how eyeglasses affect reconstruction results and propose methods to compensate for these effects as on-going research.