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Vehicle scratch detection method based on video analysis

A detection method and video analysis technology, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve the problems of low detection efficiency and high false detection rate, and achieve the effect of improving accuracy and good visualization effect

Active Publication Date: 2020-05-01
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Based on the semantic segmentation network and tracking algorithm, it detects vehicles in the video through video analysis, and judges its tracking and scratching, so as to solve the problems of low detection efficiency and high false detection rate in the existing technology

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  • Vehicle scratch detection method based on video analysis
  • Vehicle scratch detection method based on video analysis
  • Vehicle scratch detection method based on video analysis

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Embodiment Construction

[0024] The specific implementation method of the vehicle scratch detection method through the video semantic segmentation technology of the present invention will be described in detail below in conjunction with the embodiments.

[0025] The vehicle scratch detection method based on video analysis of the present invention, that is, the vehicle scratch detection method through video semantic segmentation technology, specifically includes the following steps:

[0026] Step 1: Use a rectangular frame to calibrate the parking detection area 1 and the passing detection area 2 in the surveillance video. The calibration situation is as follows figure 1 ;

[0027] Step 2: Define the set of parked vehicles S={s i |i=1,2,...,I}, the set of passing vehicles G={g j |j=1,2,…,J}, where, s i Indicates the minimum circumscribed rectangle of the i-th vehicle in S, I indicates the number of elements in the parking vehicle collection, g j Indicates the minimum circumscribed rectangle of the ...

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Abstract

The invention provides a vehicle scratch detection method based on video analysis. The invention relates to a vehicle scratch detection method, in particular to a video semantic segmentation technology-based vehicle scratch detection method. A monitoring video is acquired through a monitoring camera; a semantic segmentation method is adopted to detect and obtain vehicles in a monitoring video, thevehicles are divided into passing vehicles and parking vehicles according to the obtained position information of the vehicles, and then the position relation between the passing vehicles and the parking vehicles is judged through a scratching judgment algorithm to detect vehicle scratching. The semantic segmentation network and the tracking algorithm are taken as the basis, the vehicles in the videos are detected through video analysis, tracking and scratching judgment are carried out on the vehicle, and the invention is used for solving the problems of low detection efficiency and high false detection rate in the prior art.

Description

technical field [0001] The invention relates to the technical field of video semantic segmentation, in particular to a vehicle scratch detection method based on video analysis through the video semantic segmentation technology. Background technique [0002] With the development of the times and the advancement of technology, cars have gradually become a must-have travel tool for every household. But, along with the substantial increase of vehicle quantity, the parking space quantity of roadside increases thereupon, and road width narrows, has brought hidden danger to parking vehicle being scratched by passing vehicle. It is a waste of time and manpower to find out the information of the scratched vehicle by artificially checking the surveillance video, and the cost is too high. Therefore, a method for vehicle tracking, vehicle scratch detection and storage of vehicle scratch information based on video analysis is essential. [0003] At present, in the field of detecting ve...

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06N3/04G06N3/08
CPCG06N3/08G06V20/41G06V20/49G06V10/25G06V2201/08G06N3/045
Inventor 高飞葛逸凡卢书芳陆佳炜程振波肖刚
Owner ZHEJIANG UNIV OF TECH
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