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• W3186796973 abstract "In the current situation, around 150 million hours of video are uploaded to the Internet (i.e., YouTube, Netflix, Dailymotion, Vimeo, etc.). It becomes very difficult to extract the required relevant videos from such a large data set. Semantic / context-based matching is fast but highly dependent on the correct tags assigned to the video. On the other hand, due to the large number of frames involved in the video, it is difficult to apply a context-based search to the video. We have developed a novel video retrieval system that can extract the required videos from large sets of video data. The algorithm consists of content-based adaptive shot detection and feature vector extraction from each video from the dataset. The user only needs to provide an image similar to the system input to search for any video in the dataset." @default.
• W3186796973 created "2021-08-02" @default.
• W3186796973 creator A5079946634 @default.
• W3186796973 creator A5090542264 @default.
• W3186796973 date "2021-07-19" @default.
• W3186796973 modified "2023-09-25" @default.
• W3186796973 title "Effective video retrieval system using Adaptive Shot Detection and Feature Vector Algorithm" @default.
• W3186796973 hasPublicationYear "2021" @default.
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