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A feature matching method, a target object recognition method and related hardware

A target object and feature matching technology, applied in the field of data processing, can solve the problems of slow approximate matching of face features, leakage of face feature samples, and low recognition efficiency, achieving small storage space, speed improvement, and effective The effect of privacy protection

Active Publication Date: 2022-04-22
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the case of limited resources, the approximate matching of face features is slow, resulting in low recognition efficiency
At the same time, there is a low risk of leakage of a large number of face feature samples, which cannot effectively protect private information

Method used

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  • A feature matching method, a target object recognition method and related hardware
  • A feature matching method, a target object recognition method and related hardware
  • A feature matching method, a target object recognition method and related hardware

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Embodiment Construction

[0052] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described The embodiments are only some of the embodiments in this specification, not all of them. Based on the embodiments in this specification, all other embodiments obtained by persons of ordinary skill in the art without creative work shall fall within the protection scope of this specification.

[0053] As mentioned above, the current identification principle based on feature matching is to approximately match the feature data of the user to be identified with tens of millions or even hundreds of millions of feature data samples, so as to determine the identity of the user to be identified. Obviously, this level of recognition requires face features to tak...

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Abstract

The embodiments of this specification provide a feature matching method, a target object recognition method and related hardware. Wherein, the feature matching method includes: performing hash quantization on the feature data of the first target object based on a preset residual decomposition algorithm to obtain a multi-level feature hash value corresponding to the first target object. Obtain at least a first-order feature hash value of the second target object stored in the feature library, wherein the feature hash value of the second target object stored in the feature library is based on the residual decomposition algorithm for the It is obtained by performing hash quantization on the reference feature data of the second target object. Respectively select a feature hash value of a target order from the multi-order feature hash value and the at least one-order feature hash value for approximate matching, wherein the number of the target order is less than the multi-order feature hash value The number of Hash values.

Description

technical field [0001] This document relates to the field of data processing technology, in particular to a feature matching method, a target object recognition method and related hardware. Background technique [0002] Feature matching is widely used in recognition technology. Taking the face recognition technology as an example, the current recognition principle is based on the approximate matching of the face features of the user to be identified with millions or even hundreds of millions of face feature samples to determine the identity of the user to be identified. Obviously, this level of recognition requires facial features to take up a lot of storage space, so it must be implemented on a cloud server. In the case of limited resources, the approximate matching of face features is slow, resulting in low recognition efficiency. At the same time, there is a low risk of leaking a large number of face feature samples, which cannot effectively protect private information....

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/62G06V40/16G06V10/40G06V10/75G06V10/74G06K9/62
CPCG06F21/6245G06V40/161G06V10/40G06F18/22
Inventor 张昊
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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