Product Quantization for Vector Retrieval with No Error

Andrzej Wichert

2012

Abstract

We propose a coding mechanism for less costly exact vector retrieval for data bases representing vectors. The search starts at the subspace with the lowest dimension. In this subspace, the set of all possible similar vectors is determined. In the next subspace, additional metric information corresponding to a higher dimension is used to reduce this set. We demonstrate the method performing experiments on image retrieval on one thousand gray images of the size 128×96. Our model is twelve times less complex than a list matching.

References

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Paper Citation


in Harvard Style

Wichert A. (2012). Product Quantization for Vector Retrieval with No Error . In Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8565-10-5, pages 87-92. DOI: 10.5220/0003952800870092


in Bibtex Style

@conference{iceis12,
author={Andrzej Wichert},
title={Product Quantization for Vector Retrieval with No Error},
booktitle={Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2012},
pages={87-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003952800870092},
isbn={978-989-8565-10-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Product Quantization for Vector Retrieval with No Error
SN - 978-989-8565-10-5
AU - Wichert A.
PY - 2012
SP - 87
EP - 92
DO - 10.5220/0003952800870092