Night target detection method based on millimeter wave radar and vision fusion

Abstract

The invention discloses a night target detection method based on millimeter wave radar and visual fusion. The method specifically comprises the steps of preprocessing original data based on millimeterwave radar detection, acquiring an original image corresponding to the original data by using a camera, projecting an effective target point detected by the millimeter wave radar onto the original image to generate a region of interest, conducting image brightening on the image in the region of interest, classifying effective targets in the image based on visual deep learning, and matching the target category with the track of the effective target measured by the millimeter wave radar. The camera collects original image data; meanwhile, the all-weather working characteristics of the millimeter wave radar are combined, image brightening and target detection are carried out in the region of interest generated on the image by utilizing the target reflection points, detection of targets suchas pedestrians, motorcycles and automobiles at night is realized by utilizing the advantages of visual deep learning, and the accuracy of night target detection and tracking is effectively enhanced.

Description

technical field [0001] The present invention relates to the field of unmanned driving environment perception, in particular to a nighttime target detection method based on millimeter wave radar and vision fusion. Background technique [0002] The first prerequisite for realizing unmanned driving is to perfectly detect traffic participants such as vehicles and pedestrians from the environment. Therefore, fusion perception based on cameras and millimeter-wave radar has become an indispensable part of unmanned driving perception systems. In recent years, computer vision target detection technology has developed rapidly. Through feature extraction and analysis of the images captured by the camera, the target type and bounding box in the image can be quickly classified, and tracking and motion analysis can be performed at the same time to predict the future state of the target. , so as to better plan the driving trajectory of the ego vehicle. At present, most scholars' research ...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the research on night target detection is focused on vehicle detection, mainly for vehicle light feature analysis. However, the night driving environment is very complicated, and there are still pedestrians, motorcycles, bicycles and other traffic participants on the road. Car detection is simply impossible to achieve the task of unmanned driving

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