Distance space reconstruction method based on deep learning and monocular vision

A monocular vision, distance space technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of high cost, practical difficulty, low precision, etc., and achieve accurate width, small error, and improved accuracy. Effect

Inactive Publication Date: 2018-06-01
清华大学苏州汽车研究院(吴江) +1
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Problems solved by technology

[0004] (1) Vehicle ranging technology based on binocular vision, which requires too high installation accuracy of binocular cameras and is not robust enough
[0005] (2) Vehicle ranging technology based on lidar The advantage of this technology is high ...

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  • Distance space reconstruction method based on deep learning and monocular vision
  • Distance space reconstruction method based on deep learning and monocular vision
  • Distance space reconstruction method based on deep learning and monocular vision

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[0024] The preferred embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0025] like figure 1 , 2 As shown, a distance space reconstruction method based on deep learning and monocular vision, including the following steps:

[0026] S01: Calibrate the image collected by the image acquisition module, mark the target outline, type, target tilt angle and target distance of the image, and combine each labeled data into a multi-vector array as a sample training label;

[0027] S02: Use the sample training label as the input of the deep neural network, train the deep neural network, reconstruct the spatial structure through the deep neural network, and estimate the target distance through target recognition, border regression and spatial structure regression.

[0028] The image acquisition module (single camera), installed in the middle of the front windshield of the car, collects images, and adds Gaussian noise to t...

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Abstract

The invention discloses a distance space reconstruction method based on deep learning and monocular vision. The distance space reconstruction method includes the steps of calibrating image acquired animage acquisition module, marking the target contour, the type, the target inclination angle and the target distance of the images, combining the labeling data into multi-dimensional vector arrays toserve as sample training labels; taking the sample training labels as the input of a deep neural network, training the deep neural network, reconstructing a spatial structure through the deep neuralnetwork, and estimating the target distance estimation through target recognition, frame regression and spatial structure regression. By means of the powerful nonlinear fitting function of deep learning, the distance space information of all the samples is synthesized, distance estimation is performed globally, and accuracy is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and automatic driving, and in particular relates to a distance space reconstruction method based on deep learning and monocular vision. Background technique [0002] The automatic driving system is an active safety system that can automatically control the operation of the vehicle, including driving, changing lanes, parking, etc., which improves the driving experience and comfort while ensuring driving safety. At present, the automatic driving system mainly uses sensors installed in the vehicle, such as: millimeter-wave radar, lidar, camera and ultrasonic radar, etc., to detect and recognize the driving environment, including lane lines, surrounding vehicles, pedestrians, obstacles, traffic lights, traffic signs, etc. , Safely and efficiently automatically control vehicle driving while obeying traffic rules. When automatic driving detects obstacles, it needs to avoid, and the dist...

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Application Information

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IPC IPC(8): G06K9/62G06N3/08
CPCG06N3/08G06F18/214
Inventor 张翠翠孙辉张伟
Owner 清华大学苏州汽车研究院(吴江)
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