Title :
Video shot segmentation and key frame extraction based on SIFT feature
Author_Institution :
Dept. of Electron. & Inf. Eng., Zhejiang Univ. of Media & Commun., Hangzhou, China
Abstract :
Content complexity can be defined by SIFT feature of video content. According to the differences in the content complexity and the content change ratio calculated from video content, a video shot boundary can be detected. In general, for programs with many storylines, every story takes place by turns so that the number of key frames in a story can be estimated with the method as stated above. At last, based on the video content complexity, as well as the difference between frames and the number of key frames, every key frame can be extracted from a video. The experimental results show that the proposed method can improve both the ratio of accuracy and recall in the stages of shot segmentation and key frame extraction, by using both the features of the content complexity and the content change ratio based on SIFT feature.
Keywords :
computational complexity; feature extraction; image segmentation; transforms; video signal processing; SIFT feature-based content change ratio; SIFT feature-based key frame extraction; SIFT video content; content change ratio; content complexity; key frames number; video content complexity; video extraction; video shot boundary; video shot segmentation; Complexity theory; Corporate acquisitions; Feature extraction; Humans; Mathematical model; Motion segmentation; Robustness; SIFT feature; content change ratio; content complexity; key frame extraction; shot segmentation;
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2547-9
DOI :
10.1109/IASP.2012.6425031