Computer Vision In Vehicle Technology

Author : Antonio M. López,Atsushi Imiya,Tomas Pajdla,Jose M. Álvarez
Publisher : John Wiley & Sons
Page : 216 pages
File Size : 41,8 Mb
Release : 2017-02-17
Category : Computers
ISBN : 9781118868041

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Computer Vision in Vehicle Technology by Antonio M. López,Atsushi Imiya,Tomas Pajdla,Jose M. Álvarez Pdf

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.

Author : Antonio M. López,Atsushi Imiya,Tomas Pajdla,Jose M. Álvarez
Publisher : John Wiley & Sons
Page : 215 pages
File Size : 55,7 Mb
Release : 2017-04-17
Category : Computers
ISBN : 9781118868072

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Computer Vision in Vehicle Technology by Antonio M. López,Atsushi Imiya,Tomas Pajdla,Jose M. Álvarez Pdf

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.

Author : Mahdi Rezaei,Reinhard Klette
Publisher : Springer
Page : 224 pages
File Size : 47,7 Mb
Release : 2017-02-06
Category : Mathematics
ISBN : 9783319505510

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Computer Vision for Driver Assistance by Mahdi Rezaei,Reinhard Klette Pdf

This book summarises the state of the art in computer vision-based driver and road monitoring, focussing on monocular vision technology in particular, with the aim to address challenges of driver assistance and autonomous driving systems. While the systems designed for the assistance of drivers of on-road vehicles are currently converging to the design of autonomous vehicles, the research presented here focuses on scenarios where a driver is still assumed to pay attention to the traffic while operating a partially automated vehicle. Proposing various computer vision algorithms, techniques and methodologies, the authors also provide a general review of computer vision technologies that are relevant for driver assistance and fully autonomous vehicles. Computer Vision for Driver Assistance is the first book of its kind and will appeal to undergraduate and graduate students, researchers, engineers and those generally interested in computer vision-related topics in modern vehicle design.

Author : Sumit Ranjan,Dr. S. Senthamilarasu
Publisher : Packt Publishing Ltd
Page : 320 pages
File Size : 49,6 Mb
Release : 2020-08-14
Category : Computers
ISBN : 9781838647025

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Applied Deep Learning and Computer Vision for Self-Driving Cars by Sumit Ranjan,Dr. S. Senthamilarasu Pdf

Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook Description Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries. What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is for If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.

Author : Joel Janai,Fatma Güney,Aseem Behl,Andreas Geiger
Publisher : Unknown
Page : 308 pages
File Size : 48,7 Mb
Release : 2020
Category : Automated vehicles
ISBN : 1680836897

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Computer Vision for Autonomous Vehicles by Joel Janai,Fatma Güney,Aseem Behl,Andreas Geiger Pdf

Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. This monograph attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques. Our survey includes both the historically most relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding, and end-to-end learning for autonomous driving. Towards this goal, we analyze the performance of the state of the art on several challenging benchmarking datasets, including KITTI, MOT, and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we also provide a website that allows navigating topics as well as methods and provides additional information.

Author : Mahdi Rezaei,Reinhard Klette
Publisher : Unknown
Page : 224 pages
File Size : 40,9 Mb
Release : 2017
Category : Computer vision
ISBN : 3319505505

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Computer Vision for Driver Assistance by Mahdi Rezaei,Reinhard Klette Pdf

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
Page : 162 pages
File Size : 41,9 Mb
Release : 2024-05-06
Category : Computers
ISBN : PKEY:6610000563906

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Self Driving Car by Fouad Sabry Pdf

What is Self Driving Car A self-driving car, also known as an autonomous car (AC), driverless car, robotaxi, robotic car or robo-car, is a car that is capable of operating with reduced or no human input. Self-driving cars are responsible for all driving activities, such as perceiving the environment, monitoring important systems, and controlling the vehicle, which includes navigating from origin to destination. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Self-driving car Chapter 2: Advanced driver-assistance system Chapter 3: Vehicular automation Chapter 4: Automatic parking Chapter 5: Waymo Chapter 6: Mobileye Chapter 7: History of self-driving cars Chapter 8: Tesla Autopilot Chapter 9: Cruise (autonomous vehicle) Chapter 10: Regulation of self-driving cars (II) Answering the public top questions about self driving car. (III) Real world examples for the usage of self driving car in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Self Driving Car.

Author : Hanky Sjafrie
Publisher : CRC Press
Page : 255 pages
File Size : 55,6 Mb
Release : 2019-11-27
Category : Computers
ISBN : 9781000711776

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Introduction to Self-Driving Vehicle Technology by Hanky Sjafrie Pdf

This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology, by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications, along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise, academic researchers, technology enthusiasts, and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware, software, to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM, multi-sensor data fusion, and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies, trends, and applications which companies are pursuing in this field at present as well as other technical insights from the industry.

Author : Chiranji Lal Chowdhary,G. Thippa Reddy,B. D. Parameshachari
Publisher : CRC Press
Page : 272 pages
File Size : 54,8 Mb
Release : 2022-03-10
Category : Science
ISBN : 9781000400779

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Computer Vision and Recognition Systems by Chiranji Lal Chowdhary,G. Thippa Reddy,B. D. Parameshachari Pdf

This cutting-edge volume focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. The volume also presents innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson’s disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based vehicle lane detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis.

Author : Ljubo Vlacic,M. Parent,Fumio Harashima
Publisher : Elsevier
Page : 512 pages
File Size : 41,8 Mb
Release : 2001-06-13
Category : Technology & Engineering
ISBN : 9780080534879

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Intelligent Vehicle Technologies by Ljubo Vlacic,M. Parent,Fumio Harashima Pdf

'Intelligent Vehicle Technologies' covers the growing field of intelligent technologies, from intelligent control systems to intelligent sensors. Systems such as in-car navigation devices and cruise control are already being introduced into modern vehicles, but manufacturers are now racing to develop systems such as 'smart' cruise control, on-vehicle driver information systems, collision avoidance systems, vision enhancement and roadworthiness diagnostics systems. aimed specifically at the automotive industry packed with practical examples and applications in-depth treatment written in a text book style (rather than a theoretical specialist text style)

Author : Sathiyaraj Rajendran,Munish Sabharwal,Yu-Chen Hu,Rajesh Kumar Dhanaraj,Balamurugan Balusamy
Publisher : John Wiley & Sons
Page : 208 pages
File Size : 41,6 Mb
Release : 2024-02-27
Category : Computers
ISBN : 9781119847632

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Artificial Intelligence for Autonomous Vehicles by Sathiyaraj Rajendran,Munish Sabharwal,Yu-Chen Hu,Rajesh Kumar Dhanaraj,Balamurugan Balusamy Pdf

With the advent of advanced technologies in AI, driverless vehicles have elevated curiosity among various sectors of society. The automotive industry is in a technological boom with autonomous vehicle concepts. Autonomous driving is one of the crucial application areas of Artificial Intelligence (AI). Autonomous vehicles are armed with sensors, radars, and cameras. This made driverless technology possible in many parts of the world. In short, our traditional vehicle driving may swing to driverless technology. Many researchers are trying to come out with novel AI algorithms that are capable of handling driverless technology. The current existing algorithms are not able to support and elevate the concept of autonomous vehicles. This addresses the necessity of novel methods and tools focused to design and develop frameworks for autonomous vehicles. There is a great demand for energy-efficient solutions for managing the data collected with the help of sensors. These operations are exclusively focused on non-traditional programming approaches and depend on machine learning techniques, which are part of AI. There are multiple issues that AI needs to resolve for us to achieve a reliable and safe driverless technology. The purpose of this book is to find effective solutions to make autonomous vehicles a reality, presenting their challenges and endeavors. The major contribution of this book is to provide a bundle of AI solutions for driverless technology that can offer a safe, clean, and more convenient riskless mode of transportation.

Author : Luca Venturi,Krishtof Korda
Publisher : Packt Publishing Ltd
Page : 374 pages
File Size : 47,9 Mb
Release : 2020-10-23
Category : Computers
ISBN : 9781800201934

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Hands-On Vision and Behavior for Self-Driving Cars by Luca Venturi,Krishtof Korda Pdf

A practical guide to learning visual perception for self-driving cars for computer vision and autonomous system engineers Key FeaturesExplore the building blocks of the visual perception system in self-driving carsIdentify objects and lanes to define the boundary of driving surfaces using open-source tools like OpenCV and PythonImprove the object detection and classification capabilities of systems with the help of neural networksBook Description The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field. You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller. By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers. What you will learnUnderstand how to perform camera calibrationBecome well-versed with how lane detection works in self-driving cars using OpenCVExplore behavioral cloning by self-driving in a video-game simulatorGet to grips with using lidarsDiscover how to configure the controls for autonomous vehiclesUse object detection and semantic segmentation to locate lanes, cars, and pedestriansWrite a PID controller to control a self-driving car running in a simulatorWho this book is for This book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.

Author : Sumit Ranjan,S. Senthamilarasu
Publisher : Unknown
Page : 332 pages
File Size : 52,7 Mb
Release : 2020-08-14
Category : Computers
ISBN : 1838646302

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Applied Deep Learning and Computer Vision for Self-Driving Cars by Sumit Ranjan,S. Senthamilarasu Pdf

Author : David Gerónimo,Antonio M. López
Publisher : Springer Science & Business Media
Page : 118 pages
File Size : 49,9 Mb
Release : 2013-08-31
Category : Computers
ISBN : 9781461479871

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Vision-based Pedestrian Protection Systems for Intelligent Vehicles by David Gerónimo,Antonio M. López Pdf

Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented.

Author : Robert P. Loce,Raja Bala,Mohan Trivedi
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 54,5 Mb
Release : 2017-11-08
Category : Technology & Engineering
ISBN : 9781118971635

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Computer Vision and Imaging in Intelligent Transportation Systems by Robert P. Loce,Raja Bala,Mohan Trivedi Pdf

Acts as single source reference providing readers with an overview of how computer vision can contribute to the different applications in the field of road transportation This book presents a survey of computer vision techniques related to three key broad problems in the roadway transportation domain: safety, efficiency, and law enforcement. The individual chapters present significant applications within those problem domains, each presented in a tutorial manner, describing the motivation for and benefits of the application, and a description of the state of the art. Key features: Surveys the applications of computer vision techniques to road transportation system for the purposes of improving safety and efficiency and to assist law enforcement. Offers a timely discussion as computer vision is reaching a point of being useful in the field of transportation systems. Available as an enhanced eBook with video demonstrations to further explain the concepts discussed in the book, as well as links to publically available software and data sets for testing and algorithm development. The book will benefit the many researchers, engineers and practitioners of computer vision, digital imaging, automotive and civil engineering working in intelligent transportation systems. Given the breadth of topics covered, the text will present the reader with new and yet unconceived possibilities for application within their communities.