Story Segmentation and Retrieval of News Videos in a Multi-modal Framework
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Date
2024
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Abstract
Shot segmentation, categorization, indexing, and news story formation are the most important and primary steps in building an efficient and well-sorted video storage and retrieval system. News channels have evolved as one of the primary sources of information. However, in recent times, with the increase in the number of news channels, a plethora of news content is available on air, and it has become difficult to store and retrieve the news videos effectively. Commercials are also included in a news video, containing considerably less information. These commercials are to be filtered out, and the remaining news video will be segmented meaningfully. Segmentation of news videos is a crucial process for efficient storage and categorizing of the videos. The segmented stories also facilitate the easy retrieval and finding of the desired news. In this work, we developed different algorithms for shot segmentation, categorization, indexing, and retrieval of news videos. Our methods are independent of different temporal and spatial structures of various news channels and require a minimal manual input.
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Supervisor: Bhuyan, M K
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ELECTRONICS AND ELECTRICAL ENGINEERING