Thrown object detection method and system based on semantic segmentation network

A technology for semantic segmentation and detection methods, which is applied in image analysis, image enhancement, instruments, etc., and can solve problems such as high difficulty coefficient, inability to adapt to the transportation environment, and few sample materials.
CN112053380AActive Publication Date: 2020-12-08NINGBO POLYTECHNIC
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
NINGBO POLYTECHNIC
Publication Date
2020-12-08

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Abstract

The invention discloses a thrown object detection method and system based on a semantic segmentation network, and particularly relates to the field of road detection. The system mainly comprises an offline modeling module, an online background acquisition module and an online throwing judgment module. According to the method, the thrown object is indirectly judged through judgment of the moving target instead of direct judgment of the thrown object, the pre-detection rate of the thrown object is increased, and meanwhile, the preset background image is updated by adopting double backgrounds anda background updating strategy; and through similarity judgment of the candidate judgment area and the candidate judgment area and the preset background image, double judgment is carried out, so thatthe judgment accuracy is improved.
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Description

technical field

[0001] The invention relates to the field of road detection, in particular to a method and system for detecting spilled objects based on a semantic segmentation network. Background technique

[0002] With the development of road traffic, the speed of inter-city transportation has been greatly increased. However, more and more freight vehicles have also caused many problems. In addition to frequent rear-end collisions and collisions, there are also vehicles to avoid falling cargo. Therefore, in addition to regulating driving behavior, the detection of accidental spills is also an important reference factor for traffic safety.

[0003] Most of the existing detection methods for spilled objects on traffic roads use the traditional manual feature extraction method for detection, such as SIFT corner feature, LBP texture feature, etc. This method is affected by human factors. When changing the monitoring scene, the feature Insufficient generalization ability, weak...

Claims

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