Article image re-identification method based on multi-feature information capture and correlation analysis

Abstract

An article image re-identification method based on multi-feature information capture and correlation analysis uses a convolutional layer with a space attention mechanism and a channel attention mechanism to weight an input feature map, considers the effective combination of channel and space information, not only can pay attention to important features, but also can suppress unnecessary features, and the representation of the concerns can be improved, so that better features are obtained. By using a transformer, the features after image partitioning can be better processed by utilizing a multi-head attention mechanism, richer feature information can be captured, and the correlation among the features can be considered, so that good performance can be obtained, and the efficiency of object image retrieval can be improved. According to the method, the convolutional layer with the channel attention mechanism and the space attention mechanism and the transformer with the multi-head attention mechanism are combined, relatively important features can be paid attention to globally, and fine-grained features can be better captured, so that the re-recognition performance can be well improved.

Description

technical field [0001] The invention relates to the technical field of image retrieval, in particular to an item image re-identification method based on multi-feature information capture and correlation analysis. Background technique [0002] In recent years, the rapid development of artificial intelligence, computer vision and other technologies have been widely used in various fields. With the continuous development of the information age, the combination of computer vision and item sales and management has also become a hot spot. Given a queried item image, item image re-identification is able to retrieve all images of the same item from multiple different cameras. Item re-identification technology can not only improve people's shopping experience, but also save a certain amount of cost, improve productivity, and reduce the loss rate of items. The item image re-identification system is also widely used, not only in small stores, supermarkets and other retail industries,...

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