Identification for traffic behavior

Through the combined method of radar and video sensors, traffic behavior recognition is carried out, which solves the identification accuracy problem of traditional methods under the influence of environmental factors, and achieves more efficient traffic target detection and tracking.

WO2025087122A1 Publication Date: 2025-05-01HANGZHOU HIKVISION DIGITAL TECHNOLOGY CO LTD
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Patent Information

Application Number
PCT/CN2024/125209
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2023-10-24
Filing Date
2024-10-16
Publication Date
2025-05-01

AI Technical Summary

Technical Problem

Traditional traffic behavior recognition methods rely on video image processing, which are interfered with environmental factors such as lighting and weather. The recognition range is small and the target's real speed and location information cannot be perceived. Accuracy and application are limited.

Method used

A joint method based on radar sensors and video sensors is adopted to obtain richer image feature information through the feature level fusion of radar images and video images for traffic target detection and tracking.

Benefits of technology

It improves the accuracy of traffic behavior recognition, especially under the influence of environmental factors, and can more accurately detect and track traffic targets, enhancing the ability to identify occluded targets and distant targets.

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Abstract

Disclosed in the present application are a method and apparatus for identifying a traffic behavior, and a storage medium and an electronic device. The method comprises: acquiring a radar image on the basis of a collected signal of a radar sensor, and acquiring a video image on the basis of a collected signal of a video sensor; performing feature extraction on the radar image, performing feature extraction on the video image, and performing feature fusion on a feature extraction result of the radar image and a feature extraction result of the video image, so as to obtain a fused feature; performing traffic target detection on the basis of the fused feature, so as to obtain a detection result in a real physical coordinate space; performing traffic target tracking on the basis of the detection result in the real physical coordinate space, so as to generate a target queue trajectory of the traffic target; and identifying a target traffic behavior on the basis of the target queue trajectory.
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