Dickmanns Dynamic Vision for Perception and Control of Motion

2007
ISBN: 978-1-84628-638-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 474 Seiten, eBook

This book on autonomous road-following vehicles brings together twenty years of innovation in the field. 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.

Zielgruppe

Research

Autoren/Hrsg.

Dickmanns, Ernst Dieter

Inhaltsverzeichnis

Introduction Basic Relations: Image Sequences - ‘the World’ Subjects and Subject Classes Application Domains, Missions and Situations Extraction of Visual Features Recursive State Estimation Beginnings of Spatio-temporal Road and Ego-state Recognition The Initialization Challenge in Dynamic Scene Understanding Recursive Estimation of Road Parameters and Ego-state while Cruising Perception of Crossroads Perception of Obstacles and Other Vehicles Sensor Requirements for Flexible Perception of Road Scenes Integrated Knowledge Representations for Dynamic Vision Mission Performance, Experimental Results Conclusions and Outlook

Über Autor(innen)

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.