As digitisation era will come, a large number of multimedia datas (image, video, etc.) are stored in the database by digitisation, and its retrieval system is more and more important. Video is huge in frames amount, in order to search effectively and fast, the first step will detect and examine the place where the scene changes in the video, cut apart the scene, find out the key frame from each scene, regard as analysis that the index file searches with the key frame.
The scene changes the way and divides into the abrupt and the gradual transition. But in the video, even if in the same scene, incident of often violent movements or the camera are moving etc. happens, and obscure with the gradual transition to some extent. Thus this papper gets the main component from every frame in the video using principal component analysis (PCA), reduce the noise to interfere, and classify these feauture points with support vector clustering, it is the same class that the close feature points is belonged to. If the feature points are located between two groups of different datas, represent the scene is changing slowly in the video, detect scene change by this.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-1013105-103426 |
| Date | 13 October 2005 |
| Creators | Kao, Chih-pang |
| Contributors | John Chiang, Chung-nan Lee, Yun-Lung Chang, Weichih Hsu, Yuh-Jue Chuang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1013105-103426 |
| Rights | not_available, Copyright information available at source archive |
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