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Computer vision analysis of image motion by variational methods / Amar Mitiche and J. K. Aggarwal.

By: Contributor(s): Material type: TextTextSeries: Springer topics in signal processingPublication details: Switzerland : Springer, 2014Description: vii, 207 p. ; ill. (some color)ISBN:
  • 9783319007106
Subject(s): DDC classification:
  • 23 M684 621.367
Contents:
1. Image motion processing in visual function-- 2. Background preliminaries-- 3. Optical flow estimation-- 4. Motion detection-- 5. Tracking-- 6. Optical flow three-dimensional interpretation-- Index.
Summary: This book presents a unified view of image motion analysis under the variational framework. Variational methods, rooted in physics and mechanics, but appearing in many other domains, such as statistics, control, and computer vision, address a problem from an optimization standpoint, i.e., they formulate it as the optimization of an objective function or functional. The methods of image motion analysis described in this book use the calculus of variations to minimize (or maximize) an objective functional which transcribes all of the constraints that characterize the desired motion variables.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 621.367 M684 (Browse shelf(Opens below)) Available 135540
Total holds: 0

Includes bibliographical references and index.

1. Image motion processing in visual function--
2. Background preliminaries--
3. Optical flow estimation--
4. Motion detection--
5. Tracking--
6. Optical flow three-dimensional interpretation--
Index.

This book presents a unified view of image motion analysis under the variational framework. Variational methods, rooted in physics and mechanics, but appearing in many other domains, such as statistics, control, and computer vision, address a problem from an optimization standpoint, i.e., they formulate it as the optimization of an objective function or functional. The methods of image motion analysis described in this book use the calculus of variations to minimize (or maximize) an objective functional which transcribes all of the constraints that characterize the desired motion variables.

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