Visual position recognition method and device, computer equipment and readable storage medium

A recognition method and visual technology, applied in computer components, computing, neural learning methods, etc., can solve the problem of low accuracy of visual position recognition, achieve high accuracy and improve robustness

Pending Publication Date: 2021-03-09
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Embodiments of the present application provide a visual position recognition method, a visual position recognition device, c...

Method used

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  • Visual position recognition method and device, computer equipment and readable storage medium
  • Visual position recognition method and device, computer equipment and readable storage medium
  • Visual position recognition method and device, computer equipment and readable storage medium

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Embodiment Construction

[0026] Embodiments of the present application are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary, are only for explaining the embodiments of the present application, and should not be construed as limiting the embodiments of the present application.

[0027] see figure 1 , the present application discloses a visual position recognition method, characterized in that it includes:

[0028] 011: Build an autoencoder model, which includes a sequentially connected encoder model and decoder model;

[0029] 012: Input the training image into the pre-trained VGG-16 model to output the first information of the training image;

[0030] 013: Input the training image into the autoencoder model to output the second information of the training image;...

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Abstract

The invention discloses a visual position recognition method, a visual position recognition device, computer equipment and a nonvolatile computer readable storage medium. The visual position identification method comprises the following steps: constructing an auto-encoder model, wherein the auto-encoder model comprises an encoder model and a decoder model which are connected in sequence; inputtingthe training image into a pre-trained VGG-16 model to output first information of the training image; inputting the training image into the auto-encoder model to output second information of the training image; calculating a difference value between the first information and the second information; when the difference value is smaller than a preset value, determining that training of the auto-encoder model is completed; when the difference value is greater than a preset value, modifying parameters of the auto-encoder model, and returning to the step of inputting the training image into the auto-encoder model to output second information of the training image; and carrying out visual position identification by utilizing an encoder model in the trained auto-encoder model.

Description

technical field [0001] The present application relates to the technical field of machine vision, and in particular to a visual position recognition method, a visual position recognition device, computer equipment, and a non-volatile computer-readable storage medium. Background technique [0002] Visual position recognition has important application value in many fields, for example, it can be used for closed-loop detection of SLAM system, and it can also be used for image search based on visual content, 3D modeling and vehicle navigation. Visual location recognition faces many challenges, such as climate, environmental changes caused by lighting, dynamic object occlusion, different angles of content captured by cameras, and real-time performance of the system, all of which will affect the accuracy of visual location recognition. [0003] Currently, visual location recognition can be performed through deep learning-based visual localization methods. However, there are some p...

Claims

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Application Information

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IPC IPC(8): G06F16/51G06F16/532G06F16/583G06K9/62G06N3/04G06N3/08
CPCG06F16/51G06F16/532G06F16/583G06N3/08G06N3/045G06F18/22G06F18/214Y02A90/10
Inventor 张锲石程俊许震宇任子良康宇航高向阳
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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