@inproceedings{8f98d3d5badf4fcc8494026eac4fe68a,
title = "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.",
keywords = "High-dimensional indexing, Visual instance search, Scalable methods, Large-scale collections, Performance evaluation",
author = "Laurent Amsaleg and J{\'o}nsson, {Bj{\"o}rn Th{\'o}r} and Herwig Lejsek",
year = "2018",
month = oct,
doi = "10.1007/978-3-030-02224-2_5",
language = "English",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "59--72",
editor = "St{\'e}phane Marchand-Maillet and Silva, {Yasin N.} and Edgar Ch{\'a}vez",
booktitle = "Proceedings of the International Conference on Similarity Search and Applications (SISAP)",
address = "Germany",
}