{'fraction_non_alphanumeric': 0.01762114537444934, 'fraction_numerical': 0.004405286343612335, 'mean_word_length': 5.256880733944954, '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}}
Perceptual Grouping from Motion Cues Using Tensor Voting 1

The project addresses the problem of visual motion analysis by establishing a voting-based computational framework. We present a novel approach for matching and motion capture that recovers the dense velocity field, motion boundaries and regions from a sequence of images, based on a 4-D layered representation of data, and a voting scheme for token affinity communication. We then interpret these layers in order to generate a full dense 3-D structure of the scene, with independently moving objects segmented. Our current work involves extending the formalism to multiple frames, and improving computational efficiency.