Computer Vision in Vehicle Technology

Land, Sea, and Air

Antonio M. López, Atsushi Imiya, Tomas Pajdla, Jose M. Álvarez, Antonio M. López, Atsushi Imiya, Tomas Pajdla, Jose M. Álvarez

• Publisher: Wiley
• Year: 2017
• Print ISBN: 9781118868072
• eBook ISBN: 9781118868058
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Vision & Pattern Recognition
• Index: Computer Science

A unified view of the use of computer vision technology for different types of vehicles

Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment).

The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed.

Key features:

• Presents the latest advances in the field of computer vision and vehicle technologies in a highly informative and understandable way, including the basic mathematics for each problem.
• Provides a comprehensive summary of the state of the art computer vision techniques in vehicles from the navigation and the addressable applications points of view.
• Offers a detailed description of the open challenges and business opportunities for the immediate future in the field of vision based vehicle technologies.

This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.

Chapter 1
Computer Vision in Vehicles

Reinhard Klette

School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

This chapter is a brief introduction to academic aspects of computer vision in vehicles. It briefly summarizes basic notation and definitions used in computer vision. The chapter discusses a few visual tasks as of relevance for vehicle control and environment understanding.

1.1 Adaptive Computer Vision for Vehicles

Computer vision designs solutions for understanding the real world by using cameras. See Rosenfeld (1969), Horn (1986), Hartley and Zisserman (2003), or Klette (2014) for examples of monographs or textbooks on computer vision.

Computer vision operates today in vehicles including cars, trucks, airplanes, unmanned aerial vehicles (UAVs) such as multi-copters (see Figure 1.1 for a quadcopter), satellites, or even autonomous driving rovers on the Moon or Mars.

Figure 1.1 (a) Quadcopter. (b) Corners detected from a flying quadcopter using a modified FAST feature detector.

Courtesy of Konstantin Schauwecker

In our context, the ego-vehicle is that vehicle where the computer vision system operates in; ego-motion describes the ego-vehicle's motion in the real world.

1.1.1 Applications

Computer vision solutions are today in use in manned vehicles for improved safety or comfort, in autonomous vehicles (e.g., robots) for supporting motion or action control, and also for misusing UAVs for killing people remotely. The UAV technology has also good potentials for helping to save lives, to create three-dimensional (3D) models of the environment, and so forth. Underwater robots and unmanned sea-surface vehicles are further important applications of vision-augmented vehicles.

1.1.2 Traffic Safety and Comfort

Traffic safety is a dominant application area for computer vision in vehicles. Currently, about 1.24 million people die annually worldwide due to traffic accidents (WHO 2013), this is, on average, 2.4 people die per minute in traffic accidents. How does this compare to the numbers Western politicians are using for obtaining support for their...

Table of contents

• Cover
• Title Page
• Copyright
• Table of Contents
• List of Contributors
• Preface
• Abbreviations and Acronyms
• Chapter 1: Computer Vision in Vehicles
• Chapter 2: Autonomous Driving
• Chapter 3: Computer Vision for MAVs
• Chapter 4: Exploring the Seafloor with Underwater Robots
• Chapter 5: Vision-Based Advanced Driver Assistance Systems
• Chapter 6: Application Challenges from a Bird's-Eye View
• Chapter 7: Application Challenges of Underwater Vision
• Chapter 8: Closing Notes
• References
• Index
• End User License Agreement