Method for detecting crossing of temporary fence on construction site based on visual analysis

A construction site and visual analysis technology, applied in neural learning methods, closed-circuit television systems, biological neural network models, etc., can solve problems such as high traffic bandwidth, low efficiency, and difficult to meet the requirements of safety monitoring work

Inactive Publication Date: 2020-09-18
天津三源电力智能科技有限公司
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  • Abstract
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AI Technical Summary

Benefits of technology

This technology helps prevent accidentally entering areas where workers may be working or potentially harmful things can occur during building projects by automatically identifying potential hazards based upon their movements within specific time frames. It also includes an algorithm that tracks these activities accurately with high accuracy for better monitoring purposes.

Problems solved by technology

This patented describes how peoples' security consciousness can impact building safety during manufacturing operations by their ability to monitor and respond accordingly without being overlookable or unintended actions from outside sources like humans. However, current methods have limitations such as slow response times due to human factors that require time and resources to develop an effective solution.

Method used

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  • Method for detecting crossing of temporary fence on construction site based on visual analysis
  • Method for detecting crossing of temporary fence on construction site based on visual analysis
  • Method for detecting crossing of temporary fence on construction site based on visual analysis

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Embodiment Construction

[0032] The present invention will be described in further detail below in conjunction with the drawings and specific examples. The following examples are only descriptive, not restrictive, and cannot limit the protection scope of the present invention.

[0033] A visual analysis-based method for detecting construction site crossings over temporary fences, see figure 1 , its invention point is, comprises the following steps:

[0034] Step 1. Collect sample pictures of construction workers and temporary fences. Specifically, collect pictures through the camera, manually mark the construction workers and temporary fences in the pictures; train the deep convolutional neural target detection network, and build construction workers and temporary fence detectors. Specifically, a deep convolutional neural network is used to construct a target detection network, and then trained to obtain a detection model, that is, a detector.

[0035] Step 2. Collect the camera pictures of the construc

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Abstract

The invention relates to a method for detecting crossing of a temporary fence on a construction site based on visual analysis. The method comprises the following steps: 1, constructing a detector; 2,acquiring a camera picture of a construction site in real time, calling a detector, continuing the step 2 N seconds later if the fence is not detected, continuing the step 2 if the constructor is notdetected, and otherwise, entering the step 3; 3, initializing the constructors detected in the step 2 into a tracking target queue; 4, predicting the state of the tracking target queue; reading a real-time video frame f of the camera, and calling a detector to obtain a position d of the construction personnel in the video frame f; 5, matching the tracking result with the detection result; 6, detecting a fence position in the video frame f, judging whether an intersection point exists between the forming section and the motion trail of the construction personnel, and if so, giving an alarm; and7, rejecting the unmatched queue in the step 5, adding the unmatched d into the tracking target queue, and returning to the step 4. According to the method, intelligent construction site violation behavior detection is realized.

Description

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Claims

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Application Information

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Owner 天津三源电力智能科技有限公司
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