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Low-power-consumption real-time helmet detection method based on computer vision target detection

A technology of computer vision and target detection, which is applied in the field of computer vision and pattern recognition and intelligent transportation, can solve the problems that the helmet recognition method cannot accurately locate the target position, the performance requirements of monitoring equipment are high, and the cost of monitoring equipment is high, so as to alleviate the work Burden, identification speed, and the effect of reducing hidden dangers

Inactive Publication Date: 2021-07-16
GUANGXI NORMAL UNIV +1
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Problems solved by technology

[0003] Smart helmet recognition is very susceptible to various factors such as weather, low light, night car high beam reflections, small targets, etc., resulting in the inability of existing helmet recognition methods to accurately locate the target position. The detector model has high requirements on the performance of the monitoring equipment, and the monitoring equipment of most urban roads is relatively old at present, and the cost of replacing the monitoring equipment is very high

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  • Low-power-consumption real-time helmet detection method based on computer vision target detection
  • Low-power-consumption real-time helmet detection method based on computer vision target detection
  • Low-power-consumption real-time helmet detection method based on computer vision target detection

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Embodiment

[0035] refer to figure 1 , a low-power real-time helmet detection method based on computer vision target detection, comprising the following steps:

[0036] 1) Collection of helmet detection data sets: In daily traffic and motorcycle racing real-world scenes, various helmet-wearing and non-helmet-wearing pictures are collected to form a helmet data set. Each picture in the helmet data set contains different riding scenes Under the helmet wearing conditions, such as figure 2 As shown, the images in the helmet dataset are labeled. The image annotation information of the helmet dataset includes classification labels and positioning labels. The classification labels include helmet, head, and motorcycle information; The coordinates of the labeling frame of the head and the coordinates of the labeling frame of the motorcycle. The coordinates are expressed as the coordinates of the center point and the width and height of the labeling target frame. For training and testing a low-p...

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Abstract

The invention discloses a low-power-consumption real-time helmet detection method based on computer vision target detection, and the method is characterized in that the method comprises the following steps: 1) collecting a helmet detection data set; (2) defining a low-power-consumption real-time helmet detector model, and (3) learning the low-power-consumption real-time helmet detector model. The method is high in recognition speed and high in recognition rate, the workload of traffic management personnel can be relieved, and then the hidden danger of traffic accidents is reduced.

Description

technical field [0001] The invention relates to the technical fields of computer vision and pattern recognition and intelligent transportation, in particular to a low-power real-time helmet detection method based on computer vision target detection. Background technique [0002] With the introduction of the new policy of "one helmet and one belt" by the Traffic Management Bureau, the supervision of non-motor vehicle drivers wearing helmets has become a major problem for traffic control personnel, which has dramatically increased the workload of traffic control personnel. Artificial supervision of traffic order is a time-consuming and manpower-intensive process. During the supervision period, due to the energy consumption of traffic control personnel, it is impossible to maintain an efficient working state in real time, and negligence will inevitably occur. In addition, during holidays, traffic flow The surge has become a pain point for effective supervision of traffic order,...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/08
CPCG06N3/084G06V20/59G06V10/40G06V2201/07G06F18/24G06F18/214
Inventor 钟必能张子凯郑耀宗唐振军李先贤刘昕
Owner GUANGXI NORMAL UNIV
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