Pedestrian re-identification method based on natural language description

A pedestrian re-identification, natural language technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as large memory consumption, low text feature representation, and difficult training time for training networks.

Active Publication Date: 2020-03-24
HEBEI UNIV OF TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a pedestrian re-identification method based on natural language description, which is to design a double-branch network structure for image and natural language description. The image branch network structure uses MobileNet convolutional network for image feature extraction, natural language Describe the branch network structure to extract text features through the BiLSTM network, build a stacking loss function for the similarity measurement part between image features and text

Method used

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  • Pedestrian re-identification method based on natural language description
  • Pedestrian re-identification method based on natural language description
  • Pedestrian re-identification method based on natural language description

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Embodiment

[0103] In this embodiment, a pedestrian re-identification method based on natural language description, the specific steps are as follows:

[0104] The first step is to design the image branch network structure:

[0105] The design of the image branch network structure is to use the MobileNet convolutional network for image feature extraction. The specific operations are as follows:

[0106] First build the following MobileNet convolutional network. The MobileNet convolutional network consists of 14 layers of convolutional layers, 1 layer of pooling layer and 1 layer of fully connected layers. In addition to the first layer of the convolutional layer being the traditional convolutional layer, other The convolutional layers are all depth-separable convolutional layers, consisting of one layer of depth convolutional layer and one layer of point convolutional layer;

[0107] Then perform image feature extraction. The process is that the size of the image input into the MobileNet...

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Abstract

The invention discloses a pedestrian re-identification method based on natural language description and relates to processing of a recording carrier for identifying graphics. Specifically, the invention discloses an image and a natural language are designed to describe a double-branch network structure. In the image branch network structure a MobileNet convolutional network is adopted to carry out image feature extraction to extract text features of a natural language description branch network structure through a BiLSTM network. a stacking loss function is created for similarity measurementparts between image features and text features, and network training is carried out. A corresponding pedestrian image contained in the to-be-detected image set is searched by using a trained network to achieve pedestrian re-identification based on natural language description of a stacking loss function . The defects that in the prior art, the text feature characterization of a feature extractionpart is not high, a loss function part is difficult to train a network for a long time, and a large amount of memory is consumed in the training process are overcome.

Description

technical field [0001] The technical solution of the present invention relates to the processing for identifying graphic record carriers, in particular to a pedestrian re-identification method based on natural language description. Background technique [0002] In surveillance video, due to camera resolution and shooting angle, it is usually impossible to obtain very high-quality face pictures. In the case of face recognition failure, pedestrian re-identification has become a very important alternative technology. With the help of massive image data captured by a large number of surveillance cameras, pedestrian re-identification technology can achieve pedestrian re-identification tasks relatively accurately within a certain range, and even discover and locate the current position of pedestrians in real time, which is of great significance in the field of public security. . However, in practical applications, not all tasks that require pedestrian re-identification have imag...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/103G06V10/40G06N3/045G06F18/22G06F18/2415
Inventor 于明霍昶伟师硕郝小可于洋阎刚朱叶刘依郭迎春
Owner HEBEI UNIV OF TECH
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