Scalability of the NV-tree: Three Experiments

Abstract : The NV-tree is a scalable approximate high-dimensional indexing method specifically designed for large-scale visual instance search. In this paper, we report on three experiments designed to evaluate the performance of the NV-tree. Two of these experiments embed standard benchmarks within collections of up to 28.5 billion features, representing the largest single-server collection ever reported in the literature. The results show that indeed the NV-tree performs very well for visual instance search applications over large-scale collections.
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https://hal.inria.fr/hal-01843046
Contributor : Laurent Amsaleg <>
Submitted on : Wednesday, July 18, 2018 - 2:17:41 PM
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Laurent Amsaleg, Björn Jónsson, Herwig Lejsek. Scalability of the NV-tree: Three Experiments. SISAP 2018 - 11th International Conference on Similarity Search and Applications, Oct 2018, Lima, Peru. pp.1-14. ⟨hal-01843046⟩

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