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

Pending Publication Date: 2020-04-10
SUZHOU ZHIJIA SCI & TECH CO LTD
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Problems solved by technology

However, the traditional manual labeling method is not only time-consuming and expensive, but also because of the different subjective understanding of each labeler, it is easy to cause the problem of inconsistent labeling object categories

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  • Driving data labeling method, device and system
  • Driving data labeling method, device and system
  • Driving data labeling method, device and system

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Embodiment Construction

[0057]In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described The embodiments are only some of the embodiments in this specification, not all of them. Based on one or more embodiments in this specification, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of the embodiments of this specification.

[0058] In the control and simulation research of autonomous driving, the recognition and localization of objects is very important for the control and simulation of vehicles. However, due to the difference in image quality, environmental conditions and processing capabilities, image analysis and object labeling processing have broug...

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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.

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...

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Application Information

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IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/22G06F18/24
Inventor 江志浩崔迪潇徐生良郭立鹏陈安
Owner SUZHOU ZHIJIA SCI & TECH CO LTD
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