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Image retrieval method, device and storage medium

An image retrieval and image feature technology, which is applied in still image data retrieval, still image data indexing, still image data query, etc. , the effect of small quantization error

Active Publication Date: 2021-09-17
BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The disclosure provides an image retrieval method, device, and storage medium, which belong to the field of data retrieval, and can overcome the problems in the related art that the process of querying the nearest neighbor image features takes a long time and the accuracy of image retrieval is low

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  • Image retrieval method, device and storage medium
  • Image retrieval method, device and storage medium
  • Image retrieval method, device and storage medium

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Embodiment Construction

[0109] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. Where the following description refers to the drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the illustrative examples below are not intended to represent all implementations consistent with this disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as recited in the appended claims.

[0110] The image retrieval method provided by the present disclosure is mainly used for retrieving images with high similarity to the target image from large-scale image data, and can be specifically applied in image retrieval or video retrieval scenarios, or in scenarios such as image recommendation or video recommendation. . For example, it is applied to the fast retrieval scene of large-scale h...

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Abstract

The disclosure relates to an image retrieval method, device and storage medium, and belongs to the field of data retrieval. The method includes: obtaining the graph index structure corresponding to the image feature posting table, based on the target image feature and the graph index structure, obtaining the nearest neighbor image feature of the target image feature from the image feature posting table, and obtaining the nearest neighbor image feature corresponding Candidate image set; Based on the residual feature codebook, the residual feature between the target image feature and the nearest neighbor image feature is quantized by product to obtain the coding of the residual feature. The residual feature codebook adopts the optimal product quantization method The product is obtained by quantizing the sample residual features of a plurality of first sample images; based on the encoding of the residual features and the encoding of the candidate residual features of the candidate images in the candidate image set, the candidate image is obtained from the candidate image set as an image retrieval result . In this way, the accuracy of image retrieval can be improved on the premise of ensuring the efficiency of image retrieval.

Description

technical field [0001] The present disclosure relates to the field of data retrieval, and in particular, to an image retrieval method, device and storage medium. Background technique [0002] In the field of image retrieval, the nearest neighbor (NN, Nearest Neighbor) retrieval method is usually used for image retrieval. The nearest neighbor retrieval refers to finding the image most similar to the target image from the image database as the nearest neighbor image according to the similarity of the images. However, with the continuous increase of image and video resources on the Internet, facing the huge amount of data and high-dimensional image information, NN retrieval has been unable to obtain the ideal retrieval effect and acceptable retrieval time. Based on this, the researchers proposed a ANN (Approximate Nearest Neighbor) retrieval method. ANN retrieval refers to the use of the characteristics of clustered aggregation distribution between images after the increase of...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/51G06F16/53G06F16/583
CPCG06F16/51G06F16/53G06F16/583
Inventor 杨杰袁勇李岩刘岸
Owner BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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