Label-based automatic alignment of video with narrative sentences

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In this paper we consider videos (e.g. Hollywood movies) and their accompanying natural language descriptions in the form of narrative sentences (e.g. movie scripts without timestamps). We propose a method for temporally aligning the video frames with the sentences using both visual and textual information, which provides automatic timestamps for each narrative sentence. We compute the similarity between both types of information using vectorial descriptors and propose to cast this alignment task as a matching problem that we solve via dynamic programming. Our approach is simple to implement, highly efficient and does not require the presence of frequent dialogues, subtitles, and character face recognition. Experiments on various movies demonstrate that our method can successfully align the movie script sentences with the video frames of movies.
Publisher
European Conference on Computer Vision Committee
Issue Date
2016-10-09
Language
English
Citation

14th European Conference on Computer Vision, ECCV 2016, pp.605 - 620

DOI
10.1007/978-3-319-46604-0_43
URI
http://hdl.handle.net/10203/225726
Appears in Collection
GCT-Conference Papers(학술회의논문)
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