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A pedestrian re-identification method based on a group information loss function

A pedestrian re-identification and loss function technology, applied in neural learning methods, character and pattern recognition, instruments, etc., to achieve the effect of alleviating the phenomenon of over-fitting and accurately sorting results

Active Publication Date: 2019-05-03
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

[0004] In order to solve the problems existing in the existing pedestrian re-identification technology, the present invention proposes a pedestrian re-identification method based on the group information loss function, thereby improving the robustness and accuracy of pedestrian re-identification features

Method used

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  • A pedestrian re-identification method based on a group information loss function
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  • A pedestrian re-identification method based on a group information loss function

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Embodiment Construction

[0025] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be further described in detail below in conjunction with specific embodiments.

[0026] In the present invention, training data set D 0 It can be downloaded from http: / / www.liangzheng.org / website;

[0027] In the present invention, the construction method of the hypergraph model based on group similarity can be realized by referring to the paper: "Learning with hypergraphs: Clustering, classification, and embedding".

[0028] In the present invention, the construction method of the batch probabilistic hypergraph objective function E and the solution method of the objective function can refer to related solution algorithms of convex optimization problems.

[0029] The following examples are carried out on the premise of the technical solutions of the present invention, and detailed implementation methods and specific ope...

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Abstract

The invention discloses a pedestrian re-identification method based on a group information loss function. According to the method, the hypergraph is used for modeling, learning and expressing the group information of the training samples, and a loss function containing the group information is provided. Different from a conventional reordering method in pedestrian re-identification, the method introduces group information into a training process of a neural network. Meanwhile, the method can improve the expression ability and robustness of the trained features for different basic network structures.

Description

technical field [0001] The invention belongs to the field of image segmentation, automatic identification and target representation, and in particular relates to a pedestrian re-identification method based on a group information loss function. The model training part involves the construction of the hypergraph model and loss function and the feature learning of the convolutional neural network. Background technique [0002] Video surveillance plays a key role in security alarms, tracking suspects, missing persons and other work. However, in the process of practical application, a single camera cannot analyze the position information of pedestrians in the scene. Therefore, in practical application scenarios, it is necessary to perform pedestrian re-identification in the video surveillance network based on the query pictures of pedestrian targets. In a multi-camera surveillance network, how to carry out effective association modeling of pedestrian identity information is t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
Inventor 于慧敏曾奇勋
Owner ZHEJIANG UNIV
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