Graph based temporal aggregation for video retrieval

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Abstract

Large scale video retrieval is a field of study with a lot of ongoing research. The work that has been done in this field either uses image queries from within the video dataset or iterates through videos frame by frame. These approaches are not generalized for queries from outside the dataset and do not scale well for large video datasets. To overcome these issues, we propose a new approach for video retrieval through image queries where an undirected graph is constructed from the combined set of frames from all videos to be searched. The node features of this graph are used in the task of video retrieval. Experimentation is done on the MSR-VTT dataset by using query images from outside the dataset. To evaluate this novel approach P@5, P@10 and P@20 metrics are calculated.

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APA

Bharadwaj, A., Srinivasan, A., Saha, A., & Natarajan, S. (2021). Graph based temporal aggregation for video retrieval. In 20th International Conferences on WWW/Internet 2021 and Applied Computing 2021 (pp. 69–76). IADIS Press. https://doi.org/10.33965/icwi_ac2021_202109l009

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