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Computer Vision in Vehicle Technology: Land, Sea, and Air
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 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
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.
Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively 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
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.
207 pages, Kindle Edition
Published February 8, 2017
6 people want to read
About the author
Antonio M. López
6 books2 followersDr. Antonio M. López is the head of the Advanced Driver Assistance Systems (ADAS) Group of the Computer Vision Center (CVC), and Associate Professor of the Computer Science Department, both from the Universitat Autònoma de Barcelona (UAB). During 2009 the ADAS group achieved the qualification of “Consolidated Research Group” (2009-SGR-71) given by the autonomic government of Catalonia. Recently, the group has renewed this qualification (2014-SGR-1506).
He received the B.Sc. degree in computer science from the Universitat Politècnica de Catalunya (UPC) in 1992, the M.Sc. degree in image processing and artificial intelligence from the Universitat Autònoma de Barcelona (UAB) in 1994, and the Ph.D. degree in 2000 from the UAB as well. Since 1992, he has been teaching in the Computer Science Department of the UAB, where he currently is an Associate Professor. In 1996, he participated in the foundation of the Computer Vision Center at the UAB, where he has held different institutional responsibilities.
He has been responsible for public and private projects with companies such as Volkswagen AG, SEAT CT, Applus+IDIADA, Samsung (Europe), Xerox (XRCE), and BBraun, and is a co-author of a large number of journal and conference papers, all in the field of computer vision (see Google scholar).
His research interests are vision-based object detection, semantic segmentation, domain adaptation, computer graphics for training computer vision models. These topics are seen as key technologies to be applied in the fields that are of high interest for Antonio, namely, ADAS and autonomous driving. Currently, Antonio is specially active in domain adaptation for objected detection, in particular, adapting models learned with computer graphics ground trouth to be applied in real-world scenarios. He has been also very active in pedestrian detection for ADAS, even publishing a book about it.
It is worth to visit the current coordinated project in which Antonio is the principal investigator, ACDC.
Currently, he is responsible of the course “software engineering lab”, where the students develop a project from "zero" working in teams of around 8 members and applying software engineering best practices.
He received the B.Sc. degree in computer science from the Universitat Politècnica de Catalunya (UPC) in 1992, the M.Sc. degree in image processing and artificial intelligence from the Universitat Autònoma de Barcelona (UAB) in 1994, and the Ph.D. degree in 2000 from the UAB as well. Since 1992, he has been teaching in the Computer Science Department of the UAB, where he currently is an Associate Professor. In 1996, he participated in the foundation of the Computer Vision Center at the UAB, where he has held different institutional responsibilities.
He has been responsible for public and private projects with companies such as Volkswagen AG, SEAT CT, Applus+IDIADA, Samsung (Europe), Xerox (XRCE), and BBraun, and is a co-author of a large number of journal and conference papers, all in the field of computer vision (see Google scholar).
His research interests are vision-based object detection, semantic segmentation, domain adaptation, computer graphics for training computer vision models. These topics are seen as key technologies to be applied in the fields that are of high interest for Antonio, namely, ADAS and autonomous driving. Currently, Antonio is specially active in domain adaptation for objected detection, in particular, adapting models learned with computer graphics ground trouth to be applied in real-world scenarios. He has been also very active in pedestrian detection for ADAS, even publishing a book about it.
It is worth to visit the current coordinated project in which Antonio is the principal investigator, ACDC.
Currently, he is responsible of the course “software engineering lab”, where the students develop a project from "zero" working in teams of around 8 members and applying software engineering best practices.
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