单目相机系统中的车辆追踪与航向估计

需积分: 8 72 浏览量更新于2024-07-17 收藏 12.79MB PDF 举报

"这篇硕士论文探讨了利用单目相机系统进行车辆跟踪与航向估计的技术，属于电气工程领域，特别是辅助驾驶系统（ADAS）的一部分。作者Fredrik Nilsson在Linköping大学电气工程系完成了这项研究，并由Per Boström-Rost和Patrik Leissner指导，Gustaf Hendeby担任评审。该论文详细阐述了如何通过单摄像头系统提高驾驶安全性和道路监控效率。高级驾驶辅助系统(ADAS)是当前研究和开发的热点，其目标是通过提供对驾驶员的支持来显著降低交通事故数量。据统计，90%的事故都与人为因素有关。ADAS利用摄像头可以提供广阔的视野，结合现代先进的图像处理技术，能够实时分析路况、识别交通标志、检测障碍物以及评估车辆的行驶方向。这篇论文的核心是车辆跟踪算法，它利用单个摄像头捕获的图像数据来追踪车辆的位置并估计其航向。这在自动驾驶和智能交通系统中具有重要应用，因为它允许系统预测车辆行为，从而提前做出决策，防止潜在危险。航向估计对于理解车辆的动态行为至关重要，尤其是在复杂的交通环境中。在论文中，作者可能详细介绍了以下关键技术： 1. 图像预处理：包括去噪、校正镜头畸变、图像增强等步骤，以准备原始图像数据供后续分析。 2. 目标检测：使用如YOLO、SSD或传统方法（如霍夫变换）来检测图像中的车辆。 3. 轨迹建立与更新：利用卡尔曼滤波器或其他估计算法，结合连续帧中的车辆检测结果，建立并更新车辆的运动轨迹。 4. 航向估计：可能通过分析车辆特征（如车头方向）的变化，或者通过车辆间的相对位置和速度来估计。 5. 实时性能优化：讨论如何在保持高精度的同时，确保算法能在实际硬件平台上实时运行。此外，论文可能还包括实验设计、数据集的使用、性能评估标准以及与其他现有方法的比较。实验部分可能展示了在不同交通场景下系统的准确性和鲁棒性。最后，作者可能对未来的研究方向和潜在改进进行了展望，强调了单目相机系统在ADAS中的持续重要性和潜力。这篇论文深入研究了单目相机系统在辅助驾驶中的应用，特别是车辆跟踪和航向估计，对提升道路交通安全和自动驾驶技术的发展具有重要意义。"

2 1 Introduction

niques, good knowledge about the surrounding environment of the vehicle can

be obtained. Vision safety systems are typically constructed with either one or

two cameras, denoted mono camera systems and stereo camera systems, respec-

tively. One of the great advantages from using a stereo camera system, instead of

a mono camera system, is the ability to gain depth information from the disparity

mapping [19]. This is exactly the same ability as the human eyes have when we

observe the world, i.e., reconstruction of 3d images. This signiﬁcantly improves

the ability to obtain information about how vehicles are e.g. oriented. One bene-

ﬁt of knowing how vehicles are oriented, and how they are rotating, is that more

information can be used when predicting the future path of the vehicles. Espe-

cially, since e.g. a vehicle has constraints that limits its movements, knowing the

orientation and angular rate can give large beneﬁts.

The lack of distance information is a challenge that must be handled when devel-

oping a mono camera system. It is however not impossible to gain some depth

information from mono camera systems. One method is to assume a width or

height of an observed object in the image. Another method is to use machine

learning algorithms to recover the depth information from images [18]. Today,

advanced driver assistance systems (adas) can fuse the information from a mono

camera system together with data from e.g. a radar system. This utilizes the

cameras capability of detecting objects in a wide ﬁeld of view together with the

distance information from the radar.

Stereo cameras seem like the obvious choice. However, they are more expensive

since more hardware is used. For a car that is already expensive, this might not be

a problem. Although, in order to improve the overall traﬃc situation more cars

must use a driving assistance system. The fact is that more than 90 % of all acci-

dents on the road are caused by the human error [15]! The cheaper mono camera

system is a competitive alternative to use in order to equip more cars with adas.

In order for the mono camera system to be a reasonable substitute for the stereo

camera system, functionality that exists in a stereo camera system must also be a

feature in the mono camera system. Thus, in order to make vision systems more

available for all car manufactures and all car models, further development of the

mono camera systems is necessary.

1.2 Purpose and Objective

The purpose of this Master’s thesis is to investigate if and how the heading of ve-

hicles can be estimated in a mono camera system. Further, the thesis shall analyse

how well the mono camera system performs compared to a stereo camera system.

From this, the thesis can preferably come up with some conclusions about the

possibilities of replacing a stereo camera system with a mono camera system.

The main idea is to research the subject and ﬁnd promising algorithms for head-

ing estimation, implement and evaluate one algorithm and compare the results

with the results from a stereo camera system. The objective can be formulated

into several questions:

剩余81页未读，继续阅读

zyzhangyue

粉丝: 32
资源: 19

单目相机系统中的车辆追踪与航向估计

Tracking Multiple People with a Multi-Camera System

Estimation with Applications to Tracking and Navigation-chapter12补充

System has not been booted with systemd as init system (PID 1).

Building a Logistics Management System with Spring Boot

github.com/easinal/target-recognition-and-tracking-of-vehicle-system

yolov8 tracking

与照相机系统设计相关的英文文献

请帮我找一些关于“基于FANUC机器人的2D视觉追踪系统”相关内容的论文

Analysis and simulation of synchronization performance of direct sequence spread spectrum system based on matlab

最新资源