Searching a Raw Video Database using Natural Language Queries

The number of videos being produced and consequently stored in databases for video streaming platforms has been increasing exponentially over time. This vast database should be easily index-able to find the requisite clip or video to match the given search specification, preferably in the form of a textual query. This work aims to provide an end-to-end pipeline to search a video database with a voice query from the end user. The pipeline makes use of Recurrent Neural Networks in combination with Convolutional Neural Networks to generate captions of the video clips present in the database.
Comment: 6 pages, 12 figures, to appear in the proceedings of the First International Conference on Advances in Electrical, Computing, Communications and Sustainable Technologies (ICAECT 2021)