Target detection method and device based on machine vision and laser radar fusion
A technology of laser radar and machine vision, which is applied in the field of target detection, can solve the problems of low detection position accuracy, detection is easily affected by the environment, etc., and achieve the effect of improving classification effect, balancing accuracy rate and missed detection rate, and improving detection accuracy
Pending Publication Date: 2022-04-26
BEIJING AEROSPACE AUTOMATIC CONTROL RES INST
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[0007] In view of the above analysis, the embodiment of the present invention aims to provide a target detection method and device based on the fusion of machine vision and laser radar, to solve the problems of low detection position accuracy and environmental influence of existing target detection methods
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[0045] The following in conjunction with the accompanying drawings to describe in detail preferred embodiments of the present invention, wherein the drawings constitute part of the present application, together with embodiments of the present invention for illustrating the principles of the present invention, is not intended to limit the scope of the present invention.
[0046] A specific embodiment of the present invention, discloses a target detection method based on machine vision fusion with lidar. as Figure 1 As shown, the target detection method based on the fusion of machine vision and lidar includes in step S102, the use of a rectangular calibration plate to calibrate the lidar and camera; in step S104, the historical image data is obtained and the obstacles in the historical image data are marked as detection targets; in step S106, The AdaBoost cascading classifier based on the combination of Haar-like feature and HOG feature is trained to obtain the trained AdaBoost cas...
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The invention relates to a target detection method and device based on machine vision and laser radar fusion, belongs to the technical field of target detection, and solves the problems that the existing target detection method is low in detection position precision and the detection is easily influenced by the environment. The method comprises the following steps: calibrating a laser radar and a camera by using a rectangular calibration plate; acquiring historical image data and marking an obstacle in the historical image data as a detection target; training an AdaBoost cascade classifier based on the combination of the Haar-like features and the HOG features by using the marked historical image data so as to obtain a trained AdaBoost cascade classifier model; inputting a to-be-detected image obtained in real time into the trained AdaBoost cascade classifier model to obtain a plurality of prediction frame detection areas; and projecting point cloud data acquired in real time to the to-be-detected image, and performing fusion discrimination on a visual detection result according to the corresponding point cloud density in the prediction frame detection area. The system is more stable in various weathers and complex environments.
Description
Technical field [0001] The present invention relates to the field of object detection technology, in particular to a target detection method and apparatus based on the fusion of machine vision and lidar. Background [0002] In recent years, with the rapid development of modern intelligent technology, intelligent object detection technology has been widely used in all walks of life; in the port industry, object detection technology is mainly used to ensure the safety of port operations and improve operational efficiency; at present, there are mainly object detection systems based on machine vision, target detection systems based on millimeter wave radar and target detection systems based on lidar, and three types of target detection systems based on a single sensor are widely used. Based on the object detection of machine vision, the data is mainly collected by high-definition cameras, and then the image data is processed to extract the region of interest, and finally the specifi...
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IPC IPC(8): G06V20/10G06V10/22G06V10/50G06V10/774G06V10/764G06V10/80G06K9/62G06T7/33G06T7/80
CPCG06T7/344G06T7/80G06T2207/10028G06T2207/20081G06T2207/30204G06T2207/30244G06F18/25G06F18/24G06F18/214
Inventor 董昊天闫威唐波郑智辉郭宸瑞王硕闫涛李钊张海荣赵玲张伯川朱泽林亓欣媛常城朱敏许敏张艺佳武鹏彭皓任子建
Owner BEIJING AEROSPACE AUTOMATIC CONTROL RES INST