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Image retrieval method based on VLAD (vector of locally aggregated descriptors) dual self-adaptation

An image retrieval and self-adaptive technology, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve high accuracy and strong adaptability

Active Publication Date: 2015-09-30
TIANYUN RONGCHUANG DATA TECH BEIJING CO LTD
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of how to quickly and adaptively calculate the clustering center and improve the retrieval accuracy in the retrieval of large-scale image data sets, the present invention proposes a dual-adaptive image retrieval method based on VLAD

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  • Image retrieval method based on VLAD (vector of locally aggregated descriptors) dual self-adaptation
  • Image retrieval method based on VLAD (vector of locally aggregated descriptors) dual self-adaptation
  • Image retrieval method based on VLAD (vector of locally aggregated descriptors) dual self-adaptation

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Embodiment Construction

[0020] Below in conjunction with accompanying drawing and specific embodiment, the image retrieval method based on VLAD dual self-adaptation of the present invention is further described:

[0021] As shown in the figure, the present invention first uses the large-scale image database to be retrieved and the rough cluster centers to calculate and save the sum of all descriptors assigned to each cluster center and the number of descriptors; then use the saved Calculate the first adaptive clustering center of the data; use the sum of descriptors, the number of corresponding descriptors and the new clustering center again to recalculate the clustering center for each query image, and obtain VLAD; Finally, the VLAD is normalized twice, and the cosine distance is used to calculate the similarity distance between the query image and the image in the database to be retrieved. After sorting, the first N images are taken as the retrieval result image set.

[0022] Its specific implement...

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Abstract

The invention discloses an image retrieval method based on VLAD (vector of locally aggregated descriptors) dual self-adaptation and solves the problem about how to quickly and effectively calculate the cluster center and improve retrieval accuracy in large-scale image data set retrieval. Firstly, a to-be-retrieved large-scale image database and rough cluster centers are utilized, and the sum of all descriptors distributed to all the cluster centers and the number of the descriptors are calculated and saved; then self-adaptive cluster centers for the first time are calculated by using the saved data; the cluster centers are recalculated for all query images by using the sum of the descriptors, the number of the descriptors and new cluster centers, and VLADs are solved; finally, two-time normalization is performed on the VLADs, similarity distances between query images and images in the to-be-retrieved database are calculated by using the cosine distance, and the first N images are taken as a retrieved result image set after sequencing. The method has great significance in improving the large-scale image retrieval accuracy.

Description

technical field [0001] The invention relates to the technical field of image retrieval, in particular to an image retrieval method based on VLAD dual self-adaptation. Background technique [0002] With the rapid development of digital technology, sensor technology and network technology, the number and content of images are becoming more and more abundant. Facing such a huge, real-time expanding, and constantly changing database, how to retrieve the relevant information that you are interested in from it is particularly important. Faced with this demand, researchers began to pay more and more attention to the effective retrieval of large-scale images. In earlier studies, researchers introduced bag-of-visual words to enhance the expressive strength of descriptors and reduce quantization loss, achieving remarkable results. However, with the continuous deepening of research and the rapid increase of image scale, the memory occupied by image descriptors is also increasing, whi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/583G06F18/23211
Inventor 雷涛吕慧高红霄
Owner TIANYUN RONGCHUANG DATA TECH BEIJING CO LTD