Shot Detection Using Genetic Edge Histogram and Object Based Video Retrieval Using Multiple Features
- 1 Anna University, India
- 2 KS Rangasamy College of Technology, India
Copyright: © 2020 R. Kanagavalli and K. Duraiswamy. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
As the usage of multimedia data increasing rapidly, how to get the video data we need efficiently become so important. Recent advances in multimedia technologies allow the capture and storage of video data with relatively inexpensive computers. Problem Statement: However, without appropriate search techniques all these data are hardly usable. Users want to query the content instead of the raw video data. Today research is focused on video retrieval. Content-based search and retrieval of video data becomes a challenging and important problem. To retrieve the content of the video the user need automatic classification and categorization of the visual content. Approach: In this study a novel algorithm is proposed for shot detection using Genetic Edge Histogram and 2-D discreate cosine transform as a feature and multiple features like color, motion, shape and SIFT are used to retrieve the similar shots. Results and Conclusion: The combination of proposed features yields good results interms of precision and recall.
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- Video retrieval
- feature extraction
- shot detection