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Multimedia Technologies for Landmark-Based Vehicle Navigation.

机译:基于地标的车辆导航的多媒体技术。

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摘要

Most existing Global Positioning System (GPS)-based vehicle navigation systems (also termed route guidance systems) utilize distance within their turn-by-turn navigation directions. For example, a system might give a voice instruction like "turn left in 0.2 mile". However, human drivers usually use landmarks to help their navigation. Some previous research has shown that there are performance-related benefits in using landmarks instead of distance for navigation. The goal of this dissertation is to develop multimedia techniques that can be used for achieving landmark-based navigation using computer vision and machine learning techniques.;This dissertation makes contributions in landmark labeling, detection, recognition and the human vehicle interfaces. Landmark labeling is essential for development of landmark recognition systems and using a landmark-based navigation system. The first contribution of this dissertation is a semi-supervised learning-based approach for labeling landmarks in images. The proposed approaches, SmartLabel and SmartLabel-2, minimize user input in labeling landmarks. Text on road signs carries much useful information for driving. The second contribution is an automatic system which detects text on road signs from driving videos. The third contribution is a novel approach for recognizing a given street landmark such as a store sign in a sequence of images. We develop a street landmark recognition system that combines salient region detection, segmentation, and object fingerprint extraction techniques. The fourth contribution is a landmark building recognition framework which is able to recognize and localize the target building in dynamic driving data. Navigation user interfaces have changed dramatically over the last decade due to available electronic maps and GPS devices. However, current navigation systems without landmarks have not fully achieved user satisfaction. The fifth contribution of this dissertation is to demonstrate the concept of landmark-based vehicle navigation on a computer display and also show a prototype using a full-windshield head-up display system.
机译:大多数现有的基于全球定位系统(GPS)的车辆导航系统(也称为路线导航系统)都利用其转弯导航方向内的距离。例如,系统可能会发出语音指令,例如“在0.2英里处左转”。但是,人类驾驶员通常使用地标来帮助其导航。先前的一些研究表明,使用地标代替距离进行导航具有与性能相关的好处。本文的目的是开发可用于利用计算机视觉和机器学习技术实现基于地标的导航的多媒体技术。本论文为地标标记,检测,识别和人车界面做出了贡献。地标标签对于开发地标识别系统和使用基于地标的导航系统至关重要。本文的主要贡献是一种基于半监督学习的图像标记方法。所提议的方法SmartLabel和SmartLabel-2在标记地标时最小化了用户输入。路标上的文字为驾驶提供了许多有用的信息。第二个贡献是一个自动系统,可以从驾驶视频中检测道路标志上的文字。第三个贡献是一种新颖的方法,用于识别图像序列中的给定街道地标,例如商店标志。我们开发了一种结合了显着区域检测,分割和对象指纹提取技术的街道地标识别系统。第四个贡献是具有里程碑意义的建筑物识别框架,该框架能够在动态驾驶数据中识别和定位目标建筑物。在过去的十年中,由于可用的电子地图和GPS设备,导航用户界面发生了巨大变化。但是,当前没有地标的导航系统尚未完全达到用户满意度。本论文的第五个贡献是在计算机显示器上演示了基于地标的车辆导航的概念,并展示了使用全挡风玻璃平视显示系统的原型。

著录项

  • 作者

    Wu, Wen.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 150 p.
  • 总页数 150
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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