Safety helmet wearing detection method and device based on single-model prediction

A detection method and safety helmet technology, applied in the field of computer vision, can solve the problem of low detection accuracy of helmet wearing

Active Publication Date: 2020-09-29
ZHEJIANG LAB
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the embodiments of the present invention is to provide a safety helmet wearing detection method and device based on single-model prediction to solve the existing problem of low safety helmet wearing detection accuracy

Method used

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  • Safety helmet wearing detection method and device based on single-model prediction
  • Safety helmet wearing detection method and device based on single-model prediction
  • Safety helmet wearing detection method and device based on single-model prediction

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Embodiment 1

[0059] figure 1 It is a flow chart of a safety helmet wearing detection method based on single model prediction provided by an embodiment of the present invention; a safety helmet wearing detection method based on single model prediction provided in this embodiment includes the following steps:

[0060] Step S101, input the original image into a deep convolutional neural network, extract the apparent features of the original image in different layers of the deep convolutional neural network, and use a feature pyramid network to extract the apparent features of the original image Obtain feature maps of different scales; specifically, the following sub-steps are included:

[0061] Step S1011, using the residual network as the backbone network for feature extraction, inputting the original image into the residual network, extracting the apparent features output by the last residual block layer of the conv3, conv4, and conv5 layers, respectively Denote as {C3, C4, C5}.

[0062] ...

Embodiment 2

[0105] This embodiment provides a safety helmet wearing detection device based on single-model prediction. The device can execute any safety helmet wearing detection method based on single-model prediction provided by any embodiment of the present invention, and has the corresponding functions for executing the method. Modules and benefits. like Figure 4 As shown, the device includes: including:

[0106] The extraction module 901 is used to input the original image into a deep convolutional neural network, extract the apparent features of the original image in different layers of the deep convolutional neural network, and use a feature pyramid network in the Obtain feature maps of different scales on the apparent features;

[0107] The input-output module 903 is configured to input the feature maps of different scales into the coordinate regression network and the pedestrian recognition network, respectively output the position of the pedestrian target detected in the origi...

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Abstract

The invention discloses a safety helmet wearing detection method and device based on single-model prediction. The method comprises the following steps: inputting an original image into a deep convolutional neural network, extracting apparent characteristics of the original image from different layers of the deep convolutional neural network, and acquiring characteristic graphs of different scalesfrom the apparent characteristics by adopting a characteristic pyramid network; respectively inputting the feature maps of different scales into a coordinate regression network and a pedestrian recognition network, respectively outputting the position of a pedestrian target detected in the original image and the confidence of recognition, finding an optimal target bounding box through a non-maximum suppression method, and eliminating redundant bounding boxes; inputting the feature maps of different scales into a safety helmet wearing classification network based on an attention mechanism, andfinally obtaining a detection result whether the pedestrian target wears the safety helmet or not. Whether a worker wears a safety helmet or not in workplaces such as a factory area and a constructionsite shot by a monitoring camera is accurately recognized through a single model.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a safety helmet wearing detection method and device based on single model prediction. Background technique [0002] Wearing safety helmets is a basic safety precaution requirement in workplaces such as high temperature, power supply lines, factory areas and construction sites, and is closely related to the personal safety of construction workers. The traditional method of manual supervision will not only consume too much manpower, but also the complexity of the workplace makes supervision very difficult, which leads to frequent safety accidents caused by construction workers not wearing safety helmets. In response to this problem, it is of great necessity and practical value to use advanced artificial intelligence technology to automatically identify whether construction workers wear safety helmets. In recent years, object detection methods based on deep convolutional neural netwo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06V20/20G06N3/045G06F18/24
Inventor 郑影徐晓刚王军章依依张文广张逸
Owner ZHEJIANG LAB
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