Computer vision in vehicle technology : land, sea & air / edited by Antonio M. Lopez [and three others].

Format:

Book

Author/Creator:

López, Antonio M., 1969- author.

Imiya, Atsushi, author.

Pajdla, Tomáš, author.

Alvarez, J. M. (José M.), author.

Contributor:

López, Antonio M., 1969- editor.

Language:

English

Subjects (All):

Computer vision.

Automotive telematics.

Automated vehicles--Equipment and supplies.

Automated vehicles.

Drone aircraft--Equipment and supplies.

Drone aircraft.

Nautical instruments.

Physical Description:

1 online resource (218 pages) : color illustrations

Edition:

1st ed.

Place of Publication:

Chichester, West Sussex, United Kingdom : John Wiley & Sons, Incorporated, 2017.

Summary:

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.

Contents:

Cover

Title Page

Copyright

Contents

List of Contributors

Preface

Abbreviations and Acronyms

Chapter 1 Computer Vision in Vehicles

1.1 Adaptive Computer Vision for Vehicles

1.1.1 Applications

1.1.2 Traffic Safety and Comfort

1.1.3 Strengths of (Computer) Vision

1.1.4 Generic and Specific Tasks

1.1.5 Multi-module Solutions

1.1.6 Accuracy, Precision, and Robustness

1.1.7 Comparative Performance Evaluation

1.1.8 There Are Many Winners

1.2 Notation and Basic Definitions

1.2.1 Images and Videos

1.2.2 Cameras

1.2.3 Optimization

1.3 Visual Tasks

1.3.1 Distance

1.3.2 Motion

1.3.3 Object Detection and Tracking

1.3.4 Semantic Segmentation

1.4 Concluding Remarks

Acknowledgments

Chapter 2 Autonomous Driving

2.1 Introduction

2.1.1 The Dream

2.1.2 Applications

2.1.3 Level of Automation

2.1.4 Important Research Projects

2.1.5 Outdoor Vision Challenges

2.2 Autonomous Driving in Cities

2.2.1 Localization

2.2.2 Stereo Vision-Based Perception in 3D

2.2.3 Object Recognition

2.3 Challenges

2.3.1 Increasing Robustness

2.3.2 Scene Labeling

2.3.3 Intention Recognition

2.4 Summary

Chapter 3 Computer Vision for MAVs

3.1 Introduction

3.2 System and Sensors

3.3 Ego-Motion Estimation

3.3.1 State Estimation Using Inertial and Vision Measurements

3.3.2 MAV Pose from Monocular Vision

3.3.3 MAV Pose from Stereo Vision

3.3.4 MAV Pose from Optical Flow Measurements

3.4 3D Mapping

3.5 Autonomous Navigation

3.6 Scene Interpretation

3.7 Concluding Remarks

Chapter 4 Exploring the Seafloor with Underwater Robots

4.1 Introduction

4.2 Challenges of Underwater Imaging

4.3 Online Computer Vision Techniques

4.3.1 Dehazing

4.3.2 Visual Odometry

4.3.3 SLAM

4.3.4 Laser Scanning.

4.4 Acoustic Imaging Techniques

4.4.1 Image Formation

4.4.2 Online Techniques for Acoustic Processing

4.5 Concluding Remarks

Chapter 5 Vision-Based Advanced Driver Assistance Systems

5.1 Introduction

5.2 Forward Assistance

5.2.1 Adaptive Cruise Control (ACC) and Forward Collision Avoidance (FCA)

5.2.2 Traffic Sign Recognition (TSR)

5.2.3 Traffic Jam Assist (TJA)

5.2.4 Vulnerable Road User Protection

5.2.5 Intelligent Headlamp Control

5.2.6 Enhanced Night Vision (Dynamic Light Spot)

5.2.7 Intelligent Active Suspension

5.3 Lateral Assistance

5.3.1 Lane Departure Warning (LDW) and Lane Keeping System (LKS)

5.3.2 Lane Change Assistance (LCA)

5.3.3 Parking Assistance

5.4 Inside Assistance

5.4.1 Driver Monitoring and Drowsiness Detection

5.5 Conclusions and Future Challenges

5.5.1 Robustness

5.5.2 Cost

Chapter 6 Application Challenges from a Bird's-Eye View

6.1 Introduction to Micro Aerial Vehicles (MAVs)

6.1.1 Micro Aerial Vehicles (MAVs)

6.1.2 Rotorcraft MAVs

6.2 GPS-Denied Navigation

6.2.1 Autonomous Navigation with Range Sensors

6.2.2 Autonomous Navigation with Vision Sensors

6.2.3 SFLY: Swarm of Micro Flying Robots

6.2.4 SVO, a Visual-Odometry Algorithm for MAVs

6.3 Applications and Challenges

6.3.1 Applications

6.3.2 Safety and Robustness

6.4 Conclusions

Chapter 7 Application Challenges of Underwater Vision

7.1 Introduction

7.2 Offline Computer Vision Techniques for Underwater Mapping and Inspection

7.2.1 2D Mosaicing

7.2.2 2.5D Mapping

7.2.3 3D Mapping

7.2.4 Machine Learning for Seafloor Classification

7.3 Acoustic Mapping Techniques

7.4 Concluding Remarks

Chapter 8 Closing Notes

References

Index

EULA.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781118868058

1118868056

9781118868065

1118868064

OCLC:

975223405