Video Data Mining: Mining Semantic Patterns with temporal constraints from Movies

— For efficient video data management, ‘video data mining’ is required to discover ‘semantic patterns’ which are not only previously unknown and interesting, but also associated with semantically relevant events (‘semantic events’) in movies. In order to extract semantic patterns from a movie, we firstly represent them as a multi-stream of raw level metadata that s the semantic information of the movie. Then, regarding to the temporal characteristic of the semantic event of the movie, we extract sequential patterns which are obtained by connecting temporally close and strongly associated symbols in the multistream of raw level metadata. We also propose a parallel data mining method in order to reduce the expensive computation time. Finally, we verify whether the extracted patterns can be considered as semantic patterns or not.

• Type: Conference
• Year: 2005
• Where: ISM
• Authors: Kimiaki Shirahama, Koichi Ideno, Kuniaki Uehara
• Keywords: Data Mining, ISM 2005, Raw Level Metadata, Semantic Patterns