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- W4200156618 abstract "Teaching strategy using slides through video conference and recorded lectures are uploaded for imparting the knowledge to the learners via various online modes. There are few hurdles to understand a specific topic for learner from the video. The learners needs to put efforts and more time in listening and to reach the exact topic from the recorded lecture twice or thrice or sometimes moving to & fro the clips to understand the exact topic explained in the video for gaining knowledge. To overcome such issues, an attempt is made where the annotated indexing of lecture video to be embedded within the video for non-linear navigation to better understand the concerned topics point-wise. In this paper an algorithm to sequentially partition the lecture video into clusters and annotates the cluster by analyzing the contents of video by organizing the video in structured format which aids for efficient non-linear navigation. To access the performance of video partitioning process, we have chosen seven (7) online lecture videos of tutorials from different courses. Initially, we manually annotated required slides from the lecture videos and indexed it. Then, we used the proposed algorithm for these videos. We compared the results of extracted slides with the proposed approach using Recall and precision metrics. Our method achieved the good results when compared to other methods." @default.
- W4200156618 created "2021-12-31" @default.
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- W4200156618 date "2021-10-25" @default.
- W4200156618 modified "2023-09-26" @default.
- W4200156618 title "Segmenting lecture video into partitions by analyzing the contents of video" @default.
- W4200156618 doi "https://doi.org/10.1109/icdabi53623.2021.9655924" @default.
- W4200156618 hasPublicationYear "2021" @default.
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