Abstract
This paper introduces a video retrieval tool for the 2020 Video Browser Showdown (VBS). The tool enhances the user’s video browsing experience by ensuring full use of video analysis database constructed prior to the Showdown. Deep learning based object detection, scene text detection, scene color detection, audio classification and relation detection with scene graph generation methods have been used to construct the data. The data is composed of visual, textual, and auditory information, broadening the scope to which a user can search beyond visual information. In addition, the tool provides a simple and user-friendly interface for novice users to adapt to the tool in little time.
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CITATION STYLE
Kim, B., Shim, J. Y., Park, M., & Ro, Y. M. (2020). Deep Learning-Based Video Retrieval Using Object Relationships and Associated Audio Classes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11962 LNCS, pp. 803–808). Springer. https://doi.org/10.1007/978-3-030-37734-2_73
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