Feature similarity search implementation method and device, electronic equipment and storage medium

Abstract

The invention provides a feature similarity search implementation method and device, electronic equipment and a storage medium, and the method comprises the steps: establishing a codebook in advance based on a product quantization algorithm, establishing a plurality of user-defined functions, and loading the codebook and the user-defined functions into a database system memory; aiming at all to-be-stored characteristics, establishing an index by adopting a characteristic storage function and a codebook, inserting the index into a database, and inserting other attributes into the database; establishing a distance lookup table by adopting a distance lookup table construction function and a codebook under the condition of receiving the query feature; filtering the features in the database byusing other attributes to obtain an index meeting a preset condition; and obtaining the similarity between the query feature and the index meeting the preset condition according to the distance lookuptable, and obtaining a feature search result based on the similarity. The feature similarity search implementation method facilitates improvement of integral performance of similarity search.

Description

technical field [0001] The present application relates to the technical field of computer data processing, and in particular to a method, device, electronic equipment and storage medium for realizing feature similarity search. Background technique [0002] With the continuous development of computer technology, especially artificial intelligence technology, face retrieval or image search is applied in various scenarios, such as intelligent security, intelligent business, etc. Whether it is face retrieval or image search, it is actually a feature-based similarity search. The traditional similarity search scheme is mainly based on a specific stand-alone implementation of the approximate nearest neighbor algorithm (Approximate Nearest Neighbors, ANN). The core idea is to divide the full feature space, and according to the division method, the subspace adjacent to the target feature can be quickly locked to narrow the search range. However, the traditional similarity search tec...

AI Technical Summary

Problems solved by technology

However, the traditional similarity search technology only supports index files bound by algorithms, and the search of large amounts of data relies heavily on the Graphics Processing Unit (GPU), and the overall performance of the similarity search is low

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