{'fraction_non_alphanumeric': 0.009735744089012517, 'fraction_numerical': 0.0, 'mean_word_length': 5.7924528301886795, '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}}
Recognition of Multi-Object Events Using Attribute Grammars

We present a method for representing and recognizing visual events using attribute grammars. In contrast to conventional grammars, attribute grammars are capable of describing features that are not easily represented by finite symbols. Our approach handles multiple concurrent events involving multiple entities by associating unique object identification labels with multiple event threads. Probabilistic parsing and probabilistic conditions on the attributes are used to achieve a robust recognition system. We demonstrate the effectiveness of our method for the task of recognizing vehicle casing in parking lots and events occurring in an airport tarmac.