The application of machine vision to autonomous vehicles is an increasingly important area of research with exciting applications in industry, defense, and transportation likely in coming decades. Dynamic Vision for Perception and Control of Motion has been written by the world's leading expert on autonomous road-following vehicles and brings together twenty years of innovation in the field by Professor Dickmanns and his colleagues at the German Armed Forces university in Munich. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques. A coherent and up-to-date coverage of the subject matter is presented, with the machine vision and control aspects detailed, along with reports on the mission performance the first vehicles using these innovative techniques built at Munich. Pointers to the future development and likely applications of this hugely important field of research are presented. Dynamic Vision for Perception and Control of Motion will be a key reference for technologist working in autonomous vehicles and mobile robotics in general who wish to access the leading research in this field, as well as researchers and students working in machine vision and dynamic control interested in one of the most interesting and promising applications of these techniques.
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Details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques.
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Basic Relations: Image Sequences — “the World”.- Subjects and Subject Classes.- Application Domains, Missions, and Situations.- Extraction of Visual Features.- Recursive State Estimation.- Beginnings of Spatiotemporal Road and Ego-state Recognition.- Initialization in Dynamic Scene Understanding.- Recursive Estimation of Road Parameters and Ego State while Cruising.- Perception of Crossroads.- Perception of Obstacles and Vehicles.- Sensor Requirements for Road Scenes.- Integrated Knowledge Representations for Dynamic Vision.- Mission Performance, Experimental Results.- Conclusions and Outlook.
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The application of machine vision to autonomous vehicles is an increasingly important area of research with exciting applications in industry, defense, and transportation likely in coming decades. Dynamic Vision for Perception and Control of Motion has been written by the world's leading expert on autonomous road-following vehicles and brings together twenty years of innovation in the field by Professor Dickmanns and his colleagues at the University of the German Federal Armed Forces in Munich. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques. A coherent and up-to-date coverage of the subject matter is presented, with the machine vision and control aspects detailed, along with reports on the mission performance of the first vehicles using these innovative techniques built at Munich. Pointers to the future development and likely applications of this hugely important field of research are presented. Dynamic Vision for Perception and Control of Motion will be a key reference for technologists working in autonomous vehicles and mobile robotics in general who wish to access the leading research in this field, as well as researchers and students working in machine vision and dynamic control interested in one of the most interesting and promising applications of these techniques.
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Only up-to-date and coherent book on automous vehicles including is machine vision and control aspects The authors, Prof. Dickmanns is the world's leading researcher in the field and this book is the first he has written on his seminal research into this important field, which has has led for twenty years Includes supplementary material: sn.pub/extras
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Produktdetaljer

ISBN
9781846286377
Publisert
2007-04-12
Utgiver
Vendor
Springer London Ltd
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Biographical note

From the reviewers: "Prof. Dickmanns is THE most authoritative person in the field; there is only one Dickmanns", Stephano Soatto, UCLA.

"He is one of the world's leading experts in autonomous road-following vehicles, he has conducted seminal research that is 2nd to none. To win such an author is very prestiguous for Springer", Ulrich Zehmzow, Univ. Essex.

Professor Dr.-Ing. Ernst D. Dickmanns has been professor at the University of the Bundeswehr (FRG Army) at Munich for over 30 years. For the last two decades he and his research group have conducted the most influential work worldwide on automous vehicles, producing seminal work on perception systems for dynamic vision. He is considered to have shaped research on autonomous vehicles and to have defined the modern field in this area.