Rapid parking space detection method based on deep learning

A detection method and deep learning technology, applied in the field of driving, can solve the problems of poor adaptability to the parking space detection environment and large calculation amount of the model, and achieve good detection effect, low calculation amount, and low system cost

Active Publication Date: 2019-09-06
BEIJING INSTITUTE OF TECHNOLOGYGY +2
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Problems solved by technology

[0003] In view of the above analysis, the present invention aims to provide a fast parking space detection method based on deep le

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  • Rapid parking space detection method based on deep learning
  • Rapid parking space detection method based on deep learning
  • Rapid parking space detection method based on deep learning

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Embodiment Construction

[0055]Preferred embodiments of the present invention will be specifically described below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and are used together with the embodiments of the present invention to explain the principles of the present invention.

[0056] This embodiment discloses a fast parking space detection method based on deep learning, such as figure 1 shown, including the following steps:

[0057] Step S1, offline step: offline collection of image data containing parking spaces, establishment of training and verification data sets; training, evaluation and optimization of neural network models; the neural network model is used to carry out semantic analysis of parking space boundaries in image data segmentation;

[0058] Its establishment process includes:

[0059] 1) Collect multiple sets of image data including parking spaces offline, and mark the sideline areas of the parking spaces in...

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Abstract

The invention relates to a rapid parking space detection method based on deep learning, belongs to the technical field of driving, and is used for solving the problems of poor parking space detectionenvironment adaptability and large model calculation amount, and the method comprises the steps: an offline step: offline collecting image data including parking spaces, and establishing a training and verification data set; training, evaluating and optimizing a neural network model, wherein the neural network model is used for performing semantic segmentation on parking space sidelines in the image data; an online steps: collecting image data containing parking spaces online, carrying out semantic segmentation on parking space side boundary lines through a trained neural network model to obtain parking space side boundary masks, carrying out fitting, clustering and combination on the obtained side boundary masks, and obtaining a geometrical shape composed of the side boundaries; and according to a set shape discrimination condition, screening the geometrical shape to determine the parking space. The method is high in environmental adaptability; the size of the adopted model is very small, the calculation amount is low, and the requirement for calculation resources is low; and the system is low in cost and has large-scale application potential.

Description

technical field [0001] The invention relates to the technical field of driving, in particular to a fast parking space detection method based on deep learning. Background technique [0002] Parking space detection and positioning are the basis of automatic parking systems and assisted parking systems. In existing methods, methods based on non-deep learning rely on manual extraction of parking space sideline features for parking space detection, which has poor adaptability to the environment. For example, in There are problems with the detection system failing when the markings on the sidelines of the parking spaces are not clear, the shadows of buildings, reflections caused by stagnant water, and blurred cameras. The method based on deep learning usually has a large model size, a large amount of calculation, and high requirements for computing equipment. The high system cost is not conducive to large-scale application and promotion on vehicles. Methods with robust detection ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V20/586G06V20/588G06N3/045
Inventor 陈慧岩陈建松熊光明黄书昊齐建永龚建伟吴绍斌
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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