Fast Summarization of User-Generated Videos Using Semantic, Emotional and Quality Clues
نویسندگان
چکیده
This paper introduces a novel approach for fast summarization of user-generated videos (UGV). Different from other types of videos where the semantic contents may vary greatly over time, most UGVs contain only a single shot with relatively consistent high-level semantics and emotional content. Therefore, a few representative segments are generally sufficient for a summary, which can be selected based on the segment-level semantic and emotional recognition results. In addition, due to the poor shooting quality of many UGVs, factors such as camera shaking and lighting condition are also considered to achieve more pleasant summaries.
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