{'fraction_non_alphanumeric': 0.017881705639614855, 'fraction_numerical': 0.002751031636863824, 'mean_word_length': 5.558558558558558, '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}}
A hybrid approach for summarization of cricket videos

This study proposes an automatic method for key-events detection and summarization for cricket videos, particularly because of the longest match durations, broadcasting time concerns and largely available multimedia content. In the proposed work, first rule-based induction is applied to detect excited audio clips in cricket videos, and then a decision tree framework is designed for video summarization. The proposed method evaluated on a diverse dataset with average accuracy of 95% signifies the effectiveness in terms of video summarization. Hence, the cricket videos can reliably be broadcasted over the low-bandwidth networks and transmission with time constraints.