Automatic detection of slide transitions in lecture videos

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This paper presents a method to automatically detect slide changes in lecture videos. For accurate detection, the regions capturing slide images are first identified from video frames. Then, SIFT features are extracted from the regions, which are invariant to image scaling and rotation. These features are used to compare similarity between frames. If the similarity is smaller than a threshold, slide transition is detected. The threshold is estimated based on the mean and standard deviation of sample frames' similarities. Using this method, high detection accuracy can be obtained without any supplementary slide images. The proposed method also supports detection of backward slide transitions that occur when a speaker returns to a previous slide to emphasize its contents. In experiments conducted on our test collection, the proposed method showed 87 % accuracy in forward transition detection and 86 % accuracy in backward transition detection.
Publisher
SPRINGER
Issue Date
2015-09
Language
English
Article Type
Article
Citation

MULTIMEDIA TOOLS AND APPLICATIONS, v.74, no.18, pp.7537 - 7554

ISSN
1380-7501
DOI
10.1007/s11042-014-1990-6
URI
http://hdl.handle.net/10203/203934
Appears in Collection
CS-Journal Papers(저널논문)
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