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A Novel Educational Video Retrieval System Based on the Textual Information

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Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) (SoCPaR 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 417))

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Abstract

Video search is an active area of research in the field of information retrieval. The major approaches explored for video retrieval are metadata-based search and content-based video retrieval. In this manuscript, we propose a video retrieval system that will retrieve the videos based on the textual information present in the video frames. The key idea behind the proposed scheme is that the user who needs to retrieve a set of videos will give a keyword text through user consol. The video retrieval system will extract the frames from all the videos in the video pool and an optical character recognition module extracts the text information from each of the frames. The presence of search keywords in each frame will be analysed using the pattern matching technique. The number of times a search keyword is present in a video will decide the rank of that particular video in the final search results. To reduce the time requirement of the video retrieval operation, we have considered one frame that belongs to a scene. A video may consist of several scenes, some of the absolute differences between the reference frame and the frames video will determine the scene changes. The experimental study of the proposed scheme is carried out on the videos downloaded from National Programme on Technology Enhanced Learning (NPTEL) website. The proposed scheme will be useful to academicians to search the videos of a particular topic. The results on a limited video dataset show that the proposed scheme is performing well in real-time situations.

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Correspondence to V. M. Manikandan .

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Ravi, S., Chauhan, S., Yadlapallii, S.H., Jagruth, K., Manikandan, V.M. (2022). A Novel Educational Video Retrieval System Based on the Textual Information. In: Abraham, A., et al. Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021). SoCPaR 2021. Lecture Notes in Networks and Systems, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-030-96302-6_47

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