# Large-Scale Query-by-Image Video Retrieval Using Bloom Filters

arXiv: https://arxiv.org/abs/1604.07939 · HTML: https://mlsanity.com/paper/1604.07939/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2016.

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## Abstract (arXiv)

We consider the problem of using image queries to retrieve videos from a database. Our focus is on large-scale applications, where it is infeasible to index each database video frame independently. Our main contribution is a framework based on Bloom filters, which can be used to index long video segments, enabling efficient image-to-video comparisons. Using this framework, we investigate several retrieval architectures, by considering different types of aggregation and different functions to encode visual information -- these play a crucial role in achieving high performance. Extensive experiments show that the proposed technique improves mean average precision by 24% on a public dataset, while being 4X faster, compared to the previous state-of-the-art.