{'fraction_non_alphanumeric': 0.01452513966480447, 'fraction_numerical': 0.0, 'mean_word_length': 5.0134228187919465, '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}}
Real-time estimation of head motion using weak perspective epipolar geometry

For face and facial expression recognition, it is necessary to estimate head motion in order to track a head continuously. This paper proposes a new method for estimating head motion using the epipolar geometry of a weak perspective projection model. In this method, first, the head region is segmented from the gradient of a luminance, by approximating the contour of the head as a circle. Then, feature points such as local extremum or saddle points of a luminance distribution are traded over successive frames. Finally, angles of rotation of the head during two successive frames are estimated from the coordinates of those feature points successfully tracked in these frames. Experiments were performed on a workstation in real time and the results showed that the method performs well in estimating head motion.