Global feature descriptor polymerization method

A technology of global feature and aggregation method, applied in the computer field, can solve the problems of Fisher vector interference, high time complexity of sub-aggregation, affecting the ability of global feature descriptor sub-discrimination, etc., so as to improve the discrimination and robustness, and reduce the time complexity. degree of effect

Active Publication Date: 2015-05-13
PEKING UNIV
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AI Technical Summary

Problems solved by technology

However, the time complexity of descriptor aggregation in the prior art is high, and the obtained Fisher vector will be disturbed by some noisy local points
For example, generally, the number of local feature descriptors of an image is not less than 1000. If all the local feature descriptors are directly used to participate in the aggregation process, the time complexity of aggregation is very high; in addition, the local feature descriptor There is still some noise in , if it participates in the aggregation of Fisher vectors, it will affect the discriminative ability of the global feature descriptor, resulting in the lack of good robustness of the global feature descriptor, thus affecting the performance of image retrieval or classification

Method used

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Embodiment Construction

[0044] figure 1 It shows a schematic flowchart of the aggregation method of the global feature descriptor provided by an embodiment of the present invention, as shown in figure 1 As shown, the aggregation method of the global feature descriptor in this embodiment is as follows.

[0045] 101. Acquire a local feature descriptor of an image to be processed.

[0046] It can be understood that, according to the method of obtaining the local feature descriptor of the image to be processed, the local feature descriptor is a visual expression of the interest point, the interest point also has the different attributes, and the important properties, such as statistical significance.

[0047] For example, in obtaining the local feature descriptor of the image to be processed, the local feature descriptor is a low-dimensional local feature descriptor obtained after dimensionality reduction is performed on each local feature descriptor using a preset dimensionality reduction matrix ;

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Abstract

The invention provides a global feature descriptor polymerization method. The global feature descriptor polymerization method includes the steps of obtaining local feature descriptors of a to-be-processed image, according to according to the significance of the local feature descriptors, ranking all the local feature descriptors, and obtaining the ranked local feature descriptors; according to interceptive values, selecting a plurality of local feature descriptors used for global feature descriptor polymerization from the ranked local feature descriptors; conducting polymerization on the multiple local feature descriptors through the adoption of a Gaussian mixture model so as to obtain a global feature descriptor of the to-be-processed image, wherein the interceptive values are obtained by training retrieved results of images in a preset image data set. By means of the method, the time complexity in the global feature descriptor polymerization process in the prior art can be reduced, and the discriminability and the robustness of the global feature descriptor are improved.

Description

technical field [0001] The invention relates to computer technology, in particular to an aggregation method of global feature descriptors. Background technique [0002] At present, there are more and more mobile visual search applications, and people in the industry aggregate local feature descriptors into global feature descriptors for image retrieval or image classification. Fisher Vector is a commonly used global feature descriptor aggregated from local feature descriptors, and Fisher Vector has achieved better performance in image retrieval and classification. [0003] In the prior art, the Fisher vector is obtained by extracting local feature descriptors of an image, and aggregating all the local feature descriptors into a Fisher vector. However, the time complexity of descriptor aggregation in the prior art is relatively high, and the obtained Fisher vector will be disturbed by some noisy local points. For example, generally, the number of local feature descriptors o...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/5838G06V10/758G06F18/22
Inventor 段凌宇林杰王哲杨爽陈杰黄铁军高文
Owner PEKING UNIV
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