This book presents methods for estimating optical flow and scene flow motion with high accuracy, focusing on the practical application of these methods in camera-based driver assistance systems. Clearly and logically structured, the book builds from basic themes to more advanced concepts, culminating in the development of a novel, accurate and robust optic flow method. Features: reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithms; investigates the use of residual images for optical flow; examines methods for deriving motion from stereo image sequences; analyses the error characteristics for motion variables, and derives scene flow metrics for movement likelihood and velocity; introduces a framework for scene flow-based moving object detection and segmentation; includes Appendices on data terms and quadratic optimization, and scene flow implementation using Euler-Lagrange equations, in addition to a helpful Glossary.
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This book presents methods for estimating optical flow and scene flow motion with high accuracy, focusing on the practical application of these methods in camera-based driver assistance systems. Features: reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithms;
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Machine Vision Systems.- Optical Flow Estimation.- Residual Images and Optical Flow Results.- Scene Flow.- Motion Metrics for Scene Flow.- Extensions of Scene Flow.- Conclusion and Outlook.
The accurate and precise estimation of three-dimensional motion vector fields in real time remains one of the key targets for the discipline of computer vision.This important text/reference presents methods for estimating optical flow and scene flow motion with high accuracy, focusing on the practical application of these methods in camera-based driver assistance systems. Clearly and logically structured, the book builds from basic themes to more advanced concepts, covering topics from variational methods and optic flow estimation, to adaptive regularization and scene flow analysis. This in-depth discussion culminates in the development of a novel, accurate and robust scene flow method for the higher-level challenges posed by real-world applications.Topics and features:Reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithmsInvestigates the use of residual images for optical flowExamines methods for deriving motion from stereo image sequencesAnalyses the error characteristics for motion variables, and derives scene flow metrics for movement likelihood and velocityIntroduces a framework for scene flow-based moving object detection and segmentation, and discusses the application of Kalman filters for propagating scene flow estimation over timeIncludes pseudo code for all important computational challengesContains Appendices on data terms and quadratic optimization, and scene flow implementation using Euler-Lagrange equations, in addition to a helpful Glossary and IndexA valuable reference for researchers and graduate students on segmentation, optical flow and scene flow, this unique book will also be of great interest to professionals involved in the development of driver assistance systems.
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Describes the computation of precise and accurate optical flow, and scene flow, in real-time applications Reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithms Includes pseudo code for all important computational challenges, and contains a Glossary Includes supplementary material: sn.pub/extras
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Produktdetaljer

ISBN
9780857299642
Publisert
2011-08-17
Utgiver
Vendor
Springer London Ltd
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet