Efficient Visual Recognition Using the Hausdorff Distance [electronic resource] / edited by William Rucklidge.

Contributor(s): Rucklidge, William [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 1173Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1996Description: XIV, 186 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540495871Subject(s): Computer science | Artificial intelligence | Computer vision | Optical pattern recognition | Computer Science | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Image Processing and Computer VisionAdditional physical formats: Printed edition:: No titleDDC classification: 006.4 LOC classification: Q337.5TK7882.P3Online resources: Click here to access online
Contents:
The Hausdorff distance -- Exact computation -- Rasterisation -- Efficient computation -- Implementations and examples -- Applications -- Conclusions.
In: Springer eBooksSummary: This book presents the theoretical aspects and practical development of a computer vision system for searching an image for a specified model object; this system is reliable, tolerates imperfections in the image and model, and is fast enough for real-world applications. A number of search techniques are evaluated. The capabilities of the author's image search system are demonstrated on a variety of examples, and applications using it to track moving objects and navigate mobile robots are shown. This book is essential reading for anybody interested in model-based object recognition.
Item type: E-BOOKS
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The Hausdorff distance -- Exact computation -- Rasterisation -- Efficient computation -- Implementations and examples -- Applications -- Conclusions.

This book presents the theoretical aspects and practical development of a computer vision system for searching an image for a specified model object; this system is reliable, tolerates imperfections in the image and model, and is fast enough for real-world applications. A number of search techniques are evaluated. The capabilities of the author's image search system are demonstrated on a variety of examples, and applications using it to track moving objects and navigate mobile robots are shown. This book is essential reading for anybody interested in model-based object recognition.

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