Clustering and Authoring of Video Shots Using Hybrid-type Self-Organizing Maps
نویسندگان
چکیده
In this paper, we discuss clustering and authoring of video shots based on a hybrid self-organizing system which uses both of video-content information and meta-data (description data) as input for Kohonen's Self-Organizing Map. Conventional contents-based methods for video shots have limitations when considering the accuracy of classi cation. We propose to improve its accuracy by generating characteristic vectors by both of DCT data and keywords of video shots. Some experimental results and their evaluations are provided.
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تاریخ انتشار 1997