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|Title:||Retrieval in large video database|
|Authors:||Ng, Foon Wai|
|Department:||Department of Computer Science|
|Supervisor:||Dr Ngo, C.W. First Reader: Wong, Hau San. Second Reader: Ip, Horace|
|Abstract:||As the hard disk space now much larger than before, many people or commercial likely to keep a huge amount of video files in the computers. However, most of them don’t know how to retrieve the required shots within the large amount of videos. Although they can write down some comments on each video, they cannot drop down comments for each shot. Many research works are done on the classification of video into predefined classes by silence, non-silence, speech and music. Of course, the number of predefined classes must be limited and usually small. This usually involves segmenting the document into meaningful units, classifying each unit into a predefined scene type. Less attention was paid to the content-based retrieval of similar video clip without the limitation of fixed and predefined classes. Therefore, it is the time to find out some approaches to solve this problem. The similarities among video clips are based preliminary on their visual and audio content. Hence, we divide the videos into two classes: color and audio. Color histogram analysis can be used to retrieve video with similar colors; audio features analysis can be used to retrieve video with similar audio contents. In this paper, I will present my work in applying different approaches and methods for audio analysis. The visual information extraction will be presented in my partner’s project report.|
|Appears in Collections:||Computer Science - Undergraduate Final Year Projects|
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