Pedestrian re-identification method and system based on multi-channel consistency features

Abstract

The invention belongs to the technical field of image processing, and relates to a pedestrian re-identification method based on multi-channel consistency features, comprising the following steps: inputting N image pairs to be matched including training data and test data and their corresponding labels 1 n , where n=1,...,N; extract the semantic feature representation and color texture spatial distribution feature representation of the input image data; obtain the consistency of the semantic feature representation and color texture spatial distribution feature representation through multi-scale feature matching Feature representation; construct a binary classifier for the obtained consistent feature representation, and output a probability representation describing the same target. The invention has the advantages of: distinguishing pedestrians by synthesizing semantic attributes and color distribution features of pedestrian images, with high precision and stable performance, and is suitable for solving the problem of pedestrian re-identification in complex scenes.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a pedestrian re-identification method based on multi-channel consistency features, in particular to a deep learning method for pedestrian re-identification combined with image semantic consistency features and color texture distribution consistency features. Background technique [0002] The task of pedestrian re-identification is to deal with the problem of cross-camera pedestrian matching. The application of this technology in the pedestrian monitoring network is reflected in pedestrian tracking, human body retrieval, etc., and has extremely huge application scenarios in the field of public security. Pedestrian semantic attribute information and pedestrian color texture distribution information are complementary to a certain extent, and they are two aspects of describing pedestrians. Combining the two features for pedestrian re-identification can make up for the defect of...

AI Technical Summary

Problems solved by technology

[0003] The semantic attribute structure information of pedestrians and the color texture distribution information of pedestrian appearance are the basic information contained in the image. For the task of pedestrian re-identification, due to the large number of scenes and the huge size of pedestrians, there are often some scenes where pedestrians have similar color texture distribution on the appearance of pedestrians, such as In some scenes, pedestrians wear uniform uniforms. On the other hand, there are many people with extremely similar body characteristics and walking habits. Therefore, previous methods that rely solely on pedestrian semantic attribute information or color texture distribution information cannot perform high-precision Pedestrian re-identification

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