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A method for person re-identification based on self-motivated discriminative feature learning

A pedestrian re-identification and feature learning technology, applied in the field of pedestrian re-identification based on self-motivated discriminative feature learning, can solve the problem of insufficient optimization of pedestrian feature learning network, and achieve the effect of solving insufficient optimization

Active Publication Date: 2021-03-05
ZHEJIANG UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a pedestrian re-identification method based on self-excited discriminative feature learning, which solves the problem of insufficient optimization of the existing pedestrian feature learning network, and achieves better than traditional network optimization based on the existing model structure. way better results

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  • A method for person re-identification based on self-motivated discriminative feature learning
  • A method for person re-identification based on self-motivated discriminative feature learning
  • A method for person re-identification based on self-motivated discriminative feature learning

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Embodiment Construction

[0053] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be noted that the following embodiments are intended to facilitate the understanding of the present invention, but do not limit it in any way.

[0054] like figure 1 As shown, a pedestrian re-identification method based on self-excited discriminative feature learning, this embodiment uses the DenseNet161 network as an example to illustrate each module.

[0055] Input: a picture of pedestrians, the input size is 256(height)*128(width).

[0056] Original network: Boost object, here DenseNet161. The DenseNet161 here has been pre-trained on the ImageNet dataset. The original network consists of several convolutional modules. Here DenseNet161 contains 4 convolution modules, each convolution module contains a Dense Block and a Transition Layer. Each Dense Block contains several convolutional units composed of BatchNormalization-ReLU-Conv l...

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Abstract

The invention discloses a pedestrian re-identification method based on self-excited discriminative feature learning, comprising: (1) selecting a pedestrian re-identification network, and adding a negative branch to the original network; (2) in the training stage, the original network Generate a classification loss function, generate an adversarial loss function and a mutually exclusive response item between the original network and the negative branch, together form the objective function, and use the stochastic gradient descent method to optimize the entire network; (3) In the testing phase, remove the negative branch , only keep the part of the original network before the classifier as the trained network model, and input the pedestrian picture to extract the feature vector test; (4) in the pedestrian retrieval stage, use the trained network model to extract each picture in the picture library The eigenvector of the pedestrian image, select the identity of the image with the highest similarity with the eigenvector of the pedestrian image to be queried as the final recognition result. The invention can improve the effect of the existing pedestrian re-identification network.

Description

technical field [0001] The invention relates to the field of computer vision and pattern classification, in particular to a pedestrian re-identification method based on self-excited discriminative feature learning. Background technique [0002] In recent years, with the emergence of a large number of surveillance cameras in public places, pedestrian re-identification technology has received more and more attention. The goal of pedestrian re-identification technology is to perform cross-camera pedestrian search, that is, given a pedestrian picture captured by a certain camera, find pictures belonging to the same identity as this picture from other cameras. Pedestrian re-identification has a wide range of applications in missing person finding and suspect tracking. In recent years, pedestrian re-identification technology has developed rapidly, but there is still a long way to go before it can be applied to actual scenes. The difficulty is caused by many aspects: changes in il...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/53G06N3/045G06F18/22
Inventor 魏振勇魏龙蔡登金仲明余正旭黄建强华先胜何晓飞
Owner ZHEJIANG UNIV
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