A flexible free-space detection system based on stereo vision

Xie, Qiwei; Liu, Ranran; Sun, Zhao; Pei, Shanshan; Cui, Feng

doi:10.1016/j.neucom.2021.05.115

Cited by 13 publications

(3 citation statements)

References 35 publications

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“…The autonomous driving application scenario uses the low-power platform FPGA (Xie et al, 2021) +Acorn RISC Machine (ARM; Linux environment), and the research and development (R&D) process adopts a PC processor (Windows environment). Online testing ensures consistency between the R&D and actual application scenarios through conformance testing and guarantees actual functional experience through time-consuming testing and online stability testing.…”

Section: Online Testmentioning

confidence: 99%

An Evaluation System Based on User Big Data Management and Artificial Intelligence for Automatic Vehicles

Pei

Zhu

2022

Journal of Organizational and End User Computing

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As artificial intelligence technique is widely used in the automatic driving system, the safety evaluation of automatic vehicles is considered to be the most important demand. Under this context, in this paper, an evaluation system, which is composed of several important evaluation projects is proposed based on big data. These indicators reflect the performance of the automatic driving system. Besides, the principle of the evaluation index and the data management scheme are explained. In terms of the evaluation projects, the online test and the offline test are included, when the former focuses on the function design that is as expected, while the latter aims to ensure the actual driving experience of the automatic driving system. The evaluated results provide optimization direction of the algorithm index. Furthermore, based on AI technology and user big data management, the system saves lots of test cost and guarantees algorithm performance and system stability.

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Section: Online Testmentioning

confidence: 99%

An Evaluation System Based on User Big Data Management and Artificial Intelligence for Automatic Vehicles

Pei

Zhu

2022

Journal of Organizational and End User Computing

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“…At present, the research on binocular stereo vision is under rapid development [1,2]. Stereo matching, as the basic technology in the field of binocular stereo vision, plays a critical role in binocular stereo vision.…”

Section: Introductionmentioning

confidence: 99%

Disparity Estimation for Multi-Scale Multi-Sensor Fusion

Sun,

Pei,

Long

et al. 2024

J. of Syst. Eng. Electron.

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The perception module of advanced driver assistance systems plays a vital role. Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer. This paper proposes a multiscale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme. A binocular stereo vision sensor composed of two cameras and a light deterction and ranging (LiDAR) sensor is used to jointly perceive the environment, and a multiscale fusion scheme is employed to improve the accuracy of the disparity map. This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors. Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.

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“…At present, the 3D measurement methods in heavy rail detection research mainly include line-structured light triangulation measurement and stereo vision measurement. Among them, the stereo vision system based on linear array cameras benefits from the advantages of a large field of view, ultra-high resolution, and high acquisition speed [ 15 ]. It has higher optical accuracy, field of view range, and data transmission efficiency and is more suitable for continuous operations and high-speed transmission of industrial product inspection sites.…”

Section: Introductionmentioning

confidence: 99%

A Binocular Color Line-Scanning Stereo Vision System for Heavy Rail Surface Detection and Correction Method of Motion Distortion

Wang,

Luo,

Niu

et al. 2024

J. Imaging

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Thanks to the line-scanning camera, the measurement method based on line-scanning stereo vision has high optical accuracy, data transmission efficiency, and a wide field of vision. It is more suitable for continuous operation and high-speed transmission of industrial product detection sites. However, the one-dimensional imaging characteristics of the line-scanning camera cause motion distortion during image data acquisition, which directly affects the accuracy of detection. Effectively reducing the influence of motion distortion is the primary problem to ensure detection accuracy. To obtain the two-dimensional color image and three-dimensional contour data of the heavy rail surface at the same time, a binocular color line-scanning stereo vision system is designed to collect the heavy rail surface data combined with the bright field illumination of the symmetrical linear light source. Aiming at the image motion distortion caused by system installation error and collaborative acquisition frame rate mismatch, this paper uses the checkerboard target and two-step cubature Kalman filter algorithm to solve the nonlinear parameters in the motion distortion model, estimate the real motion, and correct the image information. The experiments show that the accuracy of the data contained in the image is improved by 57.3% after correction.

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A flexible free-space detection system based on stereo vision

Cited by 13 publications

References 35 publications

An Evaluation System Based on User Big Data Management and Artificial Intelligence for Automatic Vehicles

An Evaluation System Based on User Big Data Management and Artificial Intelligence for Automatic Vehicles

Disparity Estimation for Multi-Scale Multi-Sensor Fusion

A Binocular Color Line-Scanning Stereo Vision System for Heavy Rail Surface Detection and Correction Method of Motion Distortion

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