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Face retrieval method and device and storage medium

A retrieval algorithm and face detection technology, applied in the field of face retrieval, can solve problems such as lack of information dimension, failure to obtain face features, and low accuracy

Pending Publication Date: 2021-09-14
北京有限元科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present disclosure provide a face retrieval method, device, and storage medium, which at least solve the problem that the traditional feature extraction method in the prior art cannot obtain better face features, while the deep learning method High-dimensional and rich face features can be obtained, but in the process of building a feature index for face features, in order to improve the retrieval rate, it is necessary to perform dimensionality reduction processing or hash coding on face features, resulting in the lack of information dimensions, resulting in Technical issues with low accuracy

Method used

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  • Face retrieval method and device and storage medium
  • Face retrieval method and device and storage medium
  • Face retrieval method and device and storage medium

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Embodiment 1

[0028] According to this embodiment, an embodiment of a face retrieval method is provided. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and, although A logical order is shown in the flowcharts, but in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0029] The method embodiments provided in this embodiment can be executed in mobile terminals, computer terminals, servers or similar computing devices. figure 1 A hardware structure block diagram of a computing device for implementing the face retrieval method is shown. like figure 1 As shown, the computing device may include one or more processors (processors may include but not limited to processing devices such as microprocessors MCUs or programmable logic devices FPGAs), memory for storing data, and memory for communication functi...

Embodiment 2

[0070] Image 6 The face retrieval device 600 according to this embodiment is shown, and the device 600 corresponds to the method according to the first aspect of the first embodiment. refer to Image 6 As shown, the device 600 includes: an acquisition module 610, configured to acquire an image to be retrieved that includes a human face of a target object; a feature extraction module 620, configured to use a feature extraction model to generate the first image corresponding to the human face in the image to be retrieved. A feature vector; a determination module 630, configured to determine a target feature vector from a plurality of second feature vectors in a preset feature database according to the first feature vector, wherein the plurality of second feature vectors are respectively preset human faces The feature vectors of a plurality of human face images in the database; and the retrieval module 640, which is used to search in the human face database according to the tar...

Embodiment 3

[0079] Figure 7 The face retrieval device 700 according to this embodiment is shown, and the device 700 corresponds to the method according to the first aspect of the first embodiment. refer to Figure 7 As shown, the device 700 includes: a processor 710; and a memory 720, connected to the processor 710, for providing the processor 710 with an instruction for processing the following processing steps: acquiring an image to be retrieved that includes a human face of a target object; using features Extracting the model to generate the first feature vector corresponding to the face in the image to be retrieved; according to the first feature vector, determining the target feature vector from a plurality of second feature vectors in the preset feature database, wherein the plurality of second The eigenvectors are the eigenvectors of a plurality of face images in the preset face database respectively; The second eigenvectors are respectively the indexes of a plurality of face im...

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Abstract

The invention discloses a face retrieval method and device and a storage medium. The method comprises the following steps: acquiring a to-be-retrieved image containing a human face of a target object; utilizing a feature extraction model to generate a first feature vector corresponding to the face in the to-be-retrieved image; according to the first feature vector, determining a target feature vector from a plurality of second feature vectors in a preset feature database, the plurality of second feature vectors being feature vectors of a plurality of face images in a preset face database; and according to the target feature vector, carrying out retrieval in a face database to obtain a retrieval result corresponding to the to-be-retrieved image, wherein a plurality of second feature vectors in the feature database are indexes, in the face database, of a plurality of face images established according to a Faiiss retrieval algorithm.

Description

technical field [0001] The present application relates to the technical field of face retrieval, in particular to a face retrieval method, device and storage medium. Background technique [0002] The rise of AI has accelerated the development of face recognition. The application of face recognition has brought more and more convenience to people, such as payment by face recognition, access control by face recognition, etc. Face recognition is also used everywhere in security, finance and other fields. visible. While face recognition is developing, it has also accumulated a large amount of face data. These massive face data have also brought new challenges to face recognition. For a given face, how to quickly and accurately from the above Finding the top N pictures with the highest similarity in the billion-level face database has become an urgent problem to be solved, which is the origin of the development of face retrieval. [0003] Face retrieval can be roughly divided i...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06F16/51G06F16/532
CPCG06F16/51G06F16/532
Inventor 唐东凯曾定衡赵立军
Owner 北京有限元科技有限公司
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