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Multi-scale generative adversarial network-based shielded pedestrian re-identification method

A pedestrian re-identification, multi-scale technology, applied in the field of computer vision, can solve the problem of pedestrian re-identification performance degradation

Active Publication Date: 2019-08-16
XIAMEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the pose estimation is inaccurate, the performance of person re-identification degrades severely

Method used

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  • Multi-scale generative adversarial network-based shielded pedestrian re-identification method
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  • Multi-scale generative adversarial network-based shielded pedestrian re-identification method

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Embodiment Construction

[0051] Below in conjunction with accompanying drawing and embodiment the method of the present invention is described in detail, present embodiment is carried out under the premise of technical solution of the present invention, has provided implementation scheme and specific operation process, but protection scope of the present invention is not limited to following the embodiment.

[0052] see figure 1 and 2 , the embodiment of the present invention includes the following steps:

[0053] 1. Prepare a training set of pedestrian images.

[0054] A1. The original pedestrian image training set is expressed as The corresponding identity label is Among them, m is the number of training samples and is a natural number; x i and y i (1≤y i ≤C) represents the pedestrian image and identity label corresponding to the i-th training sample, C represents the number of identity categories contained in the training sample set and is a natural number; the non-occluded image training ...

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Abstract

The invention discloses a multi-scale generative adversarial network-based shielded pedestrian re-identification method, and relates to a computer vision technology. The method comprises the followingsteps of preparing a pedestrian image training set; designing and training a multi-scale generative adversarial network, with the network comprising a multi-scale generator and a discriminator, withthe multi-scale generator being capable of performing a de-occlusion operation on the random occlusion area to generate a high-quality reconstructed graph; enabling a discriminator to distinguish whether the input image is a real image or a generated image; generating an expanded pedestrian image training set by using the trained multi-scale generator; designing and training a classification recognition network, wherein the network is used for performing identity classification on the input pedestrian images; and extracting features of the pedestrian images by using the trained classificationand recognition network and carrying out similarity matching.

Description

technical field [0001] The invention relates to computer vision technology, in particular to an occluded pedestrian re-identification method based on a multi-scale generation confrontation network. Background technique [0002] Person Re-identification (Person Re-identification) refers to the retrieval of pedestrian images with the same identity from a large-scale pedestrian image database given a query pedestrian image in a scene captured by multiple non-overlapping cameras. Special image retrieval tasks. Pedestrian re-identification is widely used in video surveillance, intelligent security and other fields. The occlusion problem is an important factor affecting the performance of pedestrian re-identification in actual scenes. For example, pedestrians may be occluded by other pedestrians, or by some obstacles, such as vehicles, traffic signs, walls, etc. [0003] Aiming at the problem of pedestrian re-identification in occluded scenes, some researchers proposed to use ra...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V40/10G06N3/045G06F18/22G06F18/24G06F18/214
Inventor 严严杨婉香王菡子
Owner XIAMEN UNIV
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