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Human body weight identification method and device based on bimodal feature fusion network

A feature fusion and dual-modal technology, applied in the field of computer vision human body recognition, can solve the problem of single feature information and achieve high accuracy

Pending Publication Date: 2022-04-22
ZHEJIANG LAB
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] The purpose of the embodiment of the present application is to provide a method and device for human body re-identification based on a dual-modal feature fusion network to solve the technical problem of single feature information in related technologies

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  • Human body weight identification method and device based on bimodal feature fusion network
  • Human body weight identification method and device based on bimodal feature fusion network
  • Human body weight identification method and device based on bimodal feature fusion network

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Embodiment Construction

[0056] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

[0057] The terminology used in this application is for the purpose of describing particular embodiments only, and is not intended to limit the application. As used in this application and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the term...

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Abstract

The invention discloses a human body weight identification method and device based on a bimodal feature fusion network. The method comprises the following steps: acquiring a color image of a human body to be identified and corresponding other modal images; inputting the color image and the corresponding other modal images into a trained bimodal feature fusion network, and extracting features of the to-be-recognized human body; and comparing the features of the to-be-recognized human body with features of a human body image library to obtain a recognition result of the to-be-recognized human body. Aiming at the problem of human body weight identification, the color image of the human body to be identified and the corresponding other modal images are input into the trained bimodal feature fusion network for feature extraction, and the extracted feature information amount is richer than the features extracted according to the single modal image, so that the accuracy of human body weight identification is improved. Therefore, the accuracy of human body weight identification is higher than that of human body weight identification based on a single-mode image.

Description

technical field [0001] The present application relates to the field of computer vision human body re-identification, in particular to a method and device for human body re-identification based on a dual-modal feature fusion network. Background technique [0002] Human body weight recognition technology is a key technology in the field of computer vision, which has broad application prospects and high application value. This technology plays a key role in practical application scenarios such as autonomous driving, intelligent monitoring, human-computer interaction, and intelligent robots. Relying on the body weight recognition technology, in automatic driving, the trajectory of pedestrians can be predicted, so that actions such as avoidance can be made in advance; for example, in intelligent monitoring, suspects and missing children can be quickly retrieved from a large number of videos; In the interaction, more intelligent interaction can be provided; in the intelligent rob...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V40/10G06V10/56G06V10/774G06V10/764G06V10/80G06K9/62
CPCG06F18/24G06F18/253G06F18/214
Inventor 王文胡顺达朱世强宋伟林哲远金天磊
Owner ZHEJIANG LAB