Safety belt detection method and device, electronic equipment and storage medium

A detection method and a technology for seat belts, which are applied in the fields of computers and automatic driving, can solve the problems of large errors, sparse features, and low recognition accuracy.

Pending Publication Date: 2020-10-23
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the existing schemes, the artificial naked eye method has disadvantages such as slow speed, large error, and high time and labor costs; the direct classification method based on CNN, because the safety belt target is small in the

Method used

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  • Safety belt detection method and device, electronic equipment and storage medium
  • Safety belt detection method and device, electronic equipment and storage medium
  • Safety belt detection method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] figure 1 It is a schematic flow chart of the seat belt detection method provided in Embodiment 1 of the present application. The method can be executed by a seat belt detection device or an electronic device. The device or electronic device can be implemented by software and / or hardware. The device or electronic device The device can be integrated in any smart device with network communication function. like figure 1 As shown, the safety belt detection method may include the following steps:

[0030] S101. Input the image to be recognized into a pre-trained semantic segmentation network, and perform seat belt area detection on the image to be recognized through the semantic segmentation network to obtain a seat belt detection area of ​​the image to be recognized.

[0031] In a specific embodiment of the present application, the electronic device may input the image to be recognized into a pre-trained semantic segmentation network, and perform seat belt area detection ...

Embodiment 2

[0036] figure 2 It is a schematic flow chart of the safety belt detection method provided in Embodiment 2 of the present application. like figure 2 As shown, the safety belt detection method may include the following steps:

[0037] S201. Perform image preprocessing on the image to be recognized to obtain the image to be recognized after image preprocessing.

[0038] In a specific embodiment of the present application, the electronic device may perform image preprocessing on the image to be recognized to obtain the image to be recognized after image preprocessing. In one embodiment, the electronic device may first perform scaling processing on the image to be recognized to obtain the image to be recognized after scaling processing; then perform normalization processing on the image to be recognized after scaling processing to obtain the normalized image The image to be recognized; the normalized image to be recognized is used as the image to be recognized after image prep...

Embodiment 3

[0044] image 3 It is a schematic flowchart of the safety belt detection method provided in Embodiment 3 of the present application. like image 3 As shown, the safety belt detection method may include the following steps:

[0045] S301. Perform image preprocessing on the image to be recognized to obtain the image to be recognized after image preprocessing.

[0046] S302. Input the pre-processed image to be identified into the semantic segmentation network, and perform seat belt area detection on the image to be identified after image pre-processing through the semantic segmentation network to obtain the seat belt detection area of ​​the image to be identified after image pre-processing .

[0047] S303. Input the seat belt detection area into the convolution layer in the seat belt detection network, perform a convolution operation on the seat belt detection area through the convolution layer, and obtain a feature extraction result corresponding to the convolution layer.

...

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PUM

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Abstract

The invention discloses a safety belt detection method and device, electronic equipment and a storage medium, relates to the fields of artificial intelligence, deep learning and image detection, and can be applied to the field of automatic driving. According to the specific scheme, a to-be-recognized image is input into a pre-trained semantic segmentation network, safety belt area detection is conducted on the to-be-recognized image through the semantic segmentation network, and a safety belt detection area of the to-be-recognized image is obtained; and inputting the safety belt detection areainto a pre-trained safety belt detection network, and performing safety belt detection on the safety belt detection area through the safety belt detection network to obtain a safety belt detection result corresponding to the safety belt detection area. According to the embodiment of the invention, whether the driver fastens the safety belt or not can be accurately detected, so that a vehicle supervision department can be effectively assisted in operation supervision, and a guarantee is provided for safe driving of vehicles.

Description

technical field [0001] The present application relates to the field of computer technology, and further relates to the fields of artificial intelligence, deep learning and image detection, which can be applied to the field of automatic driving, especially a safety belt detection method, device, electronic equipment and storage medium. Background technique [0002] With the continuous development of the Internet and artificial intelligence technology, more and more fields have begun to involve automatic computing and analysis, among which the field of surveillance and security is one of the most important scenarios. [0003] For public operating vehicles, such as taxis, buses, long-distance buses, etc., the driver's driving safety is particularly important due to the safety of many passengers. Therefore, many public operating vehicles have been installed with on-board monitoring cameras to facilitate the corresponding companies or regulatory authorities to monitor the driver'...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06N3/04G06N3/08
CPCG06N3/084G06V40/168G06V40/172G06V20/597G06V10/267G06N3/045
Inventor 袁宇辰沈辉
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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