Driving data labeling method, device and system

A driving data, unlabeled technology, applied in the field of driving data labeling methods, devices and systems, can solve problems such as time-consuming, high cost, inconsistent labeling object categories, etc., to reduce labeling time, improve labeling efficiency, The effect of reducing labeling costs
CN110991489APending Publication Date: 2020-04-10SUZHOU ZHIJIA SCI & TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
SUZHOU ZHIJIA SCI & TECH CO LTD
Publication Date
2020-04-10

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Abstract

The embodiment of the invention discloses a driving data labeling method, device and system. The method comprises the following steps: acquiring unlabeled driving data; utilizing a target detection model in a convolutional neural network constructed by labeled sample driving data to obtain obstacle information included in the driving data; utilizing a segmentation model in the convolutional neuralnetwork to obtain road surface recognition information included in the driving data; and based on driving data obtained by a plurality of sensors in the same area, performing matching filtering on the obstacle information and the road surface recognition information to obtain a marking result of the driving data. By utilizing the embodiment of the invention, a large amount of manpower screening and labeling cost can be saved, and the problem that a large amount of wrong labeling is easily generated in automatic labeling can be avoided, so that the data labeling accuracy can be improved whilethe data labeling quality is ensured.
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Description

technical field

[0001] The embodiments of this specification belong to the technical field of automatic driving, and in particular relate to a method, device and system for labeling driving data. Background technique

[0002] For more than a century, the emergence of automobiles has replaced traditional transportation methods, making people's lives more convenient. In recent years, with the development of science and technology, especially the rapid development of intelligent computing, research on autonomous vehicle technology has become a hot spot in various industries.

[0003] Imagery and image analysis are increasingly important in control and simulation research for autonomous driving. An important aspect of image analysis is object recognition from input image or video data. It can be seen that object recognition and localization are very important for vehicle control and simulation. However, due to the difference in image quality, environmental conditions and proc...

Claims

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