PQTable: Nonexhaustive Fast Search for Product-Quantized Codes Using Hash Tables
Yusuke Matsui, Toshihiko Yamasaki, Kiyoharu Aizawa · IEEE Transactions on Multimedia · 2017
In this paper, we propose a product quantization table (PQTable)-a fast search method for product-quantized codes via hash tables. An identifier of each database vector is associated with the slot of a hash table by using its PQ-code as a key. For querying, an input vector is PQ-encoded and hashed, and the items associated with that code are then retrieved. The proposed PQTable produces the same results as a linear PQ scan, and is 102-105times faster. Although the state-of-the-art performance can be achieved by previous inverted-indexing-based approaches, such methods require manually designed parameter setting and significant training; our PQTable is free of these limitations, and therefore offers a practical and effective solution for real-world problems. Specifically, when the vectors are highly compressed, our PQTable achieves one of the fastest search performances on a single CPU to date with significantly efficient memory usage (0.059-ms per query over 109data points with just 5.5-GB memory consumption). Finally, we show that our proposed PQTable can naturally handle the codes of an optimized product quantization (OPQTable).