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Model training and lane line prediction method, electronic equipment and automatic driving vehicle

A technology of model training and lane lines, applied in neural learning methods, biological neural network models, character and pattern recognition, etc., can solve problems such as large search space and cumbersome processing, and achieve the effect of improving efficiency

Active Publication Date: 2021-11-26
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the large search space of the vectorization parameters, the current way to obtain the vectorization parameters of the lane lines is generally to perform image perception recognition first, obtain the set of lane line pixels in the image, and then fit the lane line based on the set. The process is more cumbersome

Method used

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  • Model training and lane line prediction method, electronic equipment and automatic driving vehicle
  • Model training and lane line prediction method, electronic equipment and automatic driving vehicle
  • Model training and lane line prediction method, electronic equipment and automatic driving vehicle

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Embodiment Construction

[0038] Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0039] figure 1 A schematic diagram showing a model training method according to an embodiment of the present disclosure. Such as figure 1 As shown, the method includes:

[0040] Step S110, performing clustering based on the lane line features of each of the multiple sample images to obtain at least one feature set;

[0041] Step S120, based on the cluster center of...

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Abstract

The invention provides a model training and lane line prediction method, electronic equipment and an automatic driving vehicle, belonging to the technical field of artificial intelligence, in particular to the fields of deep learning, image processing and automatic driving. According to a specific implementation scheme, the method comprises the following steps: conducting clustering based on lane line features of each sample image in a plurality of sample images so as to obtain at least one feature set; acquiring at least one center feature based on the clustering center of each feature set in the at least one feature set; acquiring annotation data of each sample image based on offset between the lane line features of each sample image and each center feature in the at least one center feature; and based on the plurality of sample images and the annotation data of each sample image, conducting training to obtain a lane line prediction model.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, in particular to the fields of deep learning, image processing and automatic driving. Background technique [0002] Lane line recognition is an important perception technology in autonomous driving scenarios. In order to store and apply the identified lane line information conveniently, the lane line information is generally characterized by vectorization parameters. Due to the large search space of the vectorization parameters, the current way to obtain the vectorization parameters of the lane lines is generally to perform image perception recognition first, obtain the set of lane line pixels in the image, and then fit the lane line based on the set. The processing process is relatively cumbersome. Contents of the invention [0003] The present disclosure provides a model training and lane line prediction method, an electronic device and an automatic driving vehicle....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/23G06F18/214
Inventor 何雷
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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