Electric power employee safety helmet wearing automatic identification method

A technology for automatic identification and safety helmets, applied in biometric identification, neural learning methods, character and pattern recognition, etc., to achieve good real-time performance, improve learning efficiency and accuracy, and reduce difficulty

Inactive Publication Date: 2020-07-31
SHANDONG UNIV OF TECH
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  • Abstract
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  • Application Information

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Problems solved by technology

[0009] The present invention aims at the defects of the above-mentioned automatic identification method for helmet wearing in the existing electric power work site monitoring video, and provides an automatic identification method for electric power employee helmet wearing, which uses

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  • Electric power employee safety helmet wearing automatic identification method
  • Electric power employee safety helmet wearing automatic identification method
  • Electric power employee safety helmet wearing automatic identification method

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[0041] In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] combine figure 1 , an automatic identification method for electric employees wearing helmets, involving data preparation, model training and helmet detection, including the following steps:

[0043] S1. Data preparation: construct a pedestrian training sample set, a helmet training sample set and a test sample set. In order t...

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Abstract

The invention provides an electric power employee safety helmet wearing automatic identification method, and relates to the technical field of mode identification and intelligent video analysis; a pedestrian detection model taking a pedestrian training sample as input is established, and pedestrian area detection of a test sample is realized through network parameter fine tuning; an SSD safety helmet detection model taking a safety helmet training sample set as input is established, a pedestrian upper body area image obtained by the pedestrian detection model is input into the trained SSD safety helmet detection model, and real-time and high-accuracy safety helmet wearing automatic identification is realized through SSD network parameter fine adjustment. According to the electric power employee helmet wearing automatic identification method, the efficient machine learning algorithm is utilized to directly detect the target, the detection precision is prevented from being influenced bycolor and edge feature changes caused by external environment changes, and the detection precision and the detection efficiency are improved by adopting two detection model cascade application modes at the same time.

Description

technical field [0001] The invention relates to the technical field of pattern recognition and intelligent video analysis, in particular to an automatic identification method for electric power employees wearing helmets. Background technique [0002] The electric safety helmet is an important safety protection device in electric work. The electric safety helmet maintains the safety of the staff's head and avoids fatal injuries to electric workers such as electric shock and smashing injuries. At present, the work site of the power sector is usually installed with a safety production video monitoring system, which collects and stores video data through the camera, and then monitors the safety status of people or objects at the work site through manual viewing. Such a supervision process increases labor costs, and at the same time, some unnecessary safety accidents occur due to subjective factors such as fatigue and negligence of the video viewing staff. Therefore, it is neces...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06V20/52G06V2201/07G06N3/045G06F18/214
Inventor 邹国锋傅桂霞姜殿波高明亮尹丽菊王玮马立修
Owner SHANDONG UNIV OF TECH
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