CASIA OpenIR  > 毕业生  > 硕士学位论文
Thesis Advisor王欣刚
Degree Grantor中国科学院大学
Place of Conferral北京
(3)研究并实现了快速准确的前方车辆跟踪模块。本文结合卷积神经网络的方法以及基于通过检测来跟踪(tracking by detection)的相关滤波器的方法,设计并实现了一种非常快速、准确的前方车辆跟踪算法。
Other AbstractIn recent years, with the development of artificial intelligence, computer vision and deep learning, advanced driver assistant system has become a very popular research and application field. The key functions of advanced driver assistant system, including lane keeping, yaw warning, adaptive cruise control, distance measurement of leading vehicle and collision warning, all depend on monocular computer vision technologies. So the research contents of this paper have important theoretical significance and application values.
Based on the above background, the key technologies of the monocular vision in advanced driver assistant system are discussed and studied in this paper. We implement and innovate some key modules including lane detection and tracking, road and sky region recognition, vehicle detection and vehicle tracking. At the same time, based on key modules introduced above, we present a framework for leading vehicle localization and tracking, which is real-time and accurate.
Specifically, the work done and the research results obtained in this paper include the following aspects:
(1) A method to reduce the region of interest for the problem of leading vehicle localization and tracking is proposed. The method for ROI region reduction includes lane detection and tracking, road region recognition and sky region recognition.
(2) A real-time and accurate vehicle detection module is introduced in this paper. Based on the conventional object detection method of Haar-like features and cascaded adaboost classifier, and convolutional neural network, we design a real-time and accurate vehicle detection system.
(3) A fast and accurate vehicle tracking module is proposed. Based on convolutional neural network trained for vehicle detection and adaptive correlation filters for visual tracking, we propose a fast and effective vehicle tracking algorithm.
(4) A real-time and accurate system is built for the leading vehicle localization and tracking problem, combined with lane detection, road and sky recognition, vehicle detection, vehicle tracking and other modules.
In this paper, the key modules and technologies based on monocular vision in the advanced driver assistant system (ADAS) are realized. At the same time, the requirements of the system's precision and real-time performance are also met. The contents of this paper are supposed to give some consult and reference meaning for the research and practical application of the advanced driver assistant system.
Document Type学位论文
Recommended Citation
GB/T 7714
黄冠. 汽车辅助驾驶系统中的单目视觉导航关键技术研究[D]. 北京. 中国科学院大学,2016.
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汽车辅助驾驶系统中的单目视觉导航关键技术(2680KB)学位论文 暂不开放CC BY-NC-SAApplication Full Text
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