期刊
CHINA COMMUNICATIONS
卷 11, 期 2, 页码 86-94出版社
CHINA INST COMMUNICATIONS
DOI: 10.1109/CC.2014.7085388
关键词
horror video recognition; video affective; fuzzy comprehensive evolution; K-Means cluster
资金
- Jiangsu Future Networks Innovation Institute-Prospective Research Project on Future Networks [BY2013095-2-14]
- State Ethnic Affairs Commission
- Minzu University of China [K2014053]
Technique for horror video recognition is important for its application in web content filtering and surveillance, especially for preventing children from being threaten. In this paper, a novel horror video recognition algorithm based on fuzzy comprehensive evolution model is proposed. Three low-level video features are extracted as typical features, and they are video key-light, video colour energy and video rhythm. Analytic Hierarchy Process (AHP) is adopted to estimate the weights of extracted features in fuzzy evolution model. Horror evaluation (membership function) is on shot scale and it is constructed based on the knowledge that videos which share the same affective have similar low-level features. K-Means algorithm is implemented to help finding the most representative feature vectors. The experimental results demonstrate that the proposed approach has good performance in recognition precision, recall rate and F1 measure.
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