Learning-Based Video Highlights Extraction
Date Issued
2012
Date
2012
Author(s)
Lin, Keng-Sheng
Abstract
Emotion-based highlights extraction is useful for retrieval and automatic trailer generation of drama video because the rich emotion part of a drama video is often the center of attraction to the viewer. In this thesis, we formulate highlights extraction as a regression problem to extract highlight segments and to predict how strong the viewer’s emotion would be evoked by the video segments. Unlike conventional rule-based approaches that rely on heuristics, the proposed system determines the relation between drama highlights and audiovisual features by machine learning. We also examine the special characteristics of drama video and propose human face, music emotion, shot duration, and motion magnitude as feature sets for highlights extraction. Quantitative evaluation results are provided to illustrate the performance of the system.
Subjects
Affective content
highlights extraction
drama video
machine learning
regression
Type
thesis
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