Event-Driven Video Abstraction and Visualization
作者： Jeho Nam , Ahmed H. Tewfik
关键词: Video tracking 、 Computer science 、 Natural language processing 、 Scheme (programming language) 、 Abstraction (linguistics) 、 Key (cryptography) 、 Visualization 、 Smacker video 、 Artificial intelligence 、 Automatic summarization 、 Computer vision 、 Event (computing)
摘要: In this paper, we propose a new video summarization procedure that produces dynamic (video) abstract of the original sequence. Our technique compactly summarizes data by preserving its temporal characteristics (visual activity) and semantically essential information. It relies on an adaptive nonlinear sampling. The local sampling rate is directly proportional to amount visual activity in localized sub-shot units video. To get very short, yet meaningful summaries, also present event-oriented abstraction scheme, which two semantic eventss emotional dialogue violent action, are characterized abstracted into summary before all other events. If length permits, non key events then added. resulting highly compact.
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