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Springer Front-End Vision and Multi-Scale Image Analysis - Springer

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Description

Front-End Vision and Multi-Scale Image Analysis explores advanced computer vision theory and applications through multi-scale approaches implemented in Mathematica. This comprehensive resource examines optic flow computation techniques, covering gradient-based differential methods, phase-based frequency domain approaches, and correlation-based area methods for dense optic flow field calculation. Part of the Computational Imaging and Vision series (volume 27), this technical work by Springer provides in-depth analysis of image sequence processing and visual data interpretation. Ideal for researchers, computer scientists, and engineers working in machine learning, artificial intelligence, and advanced image processing, this book combines theoretical foundations with practical implementations to address complex problems in front-end vision systems and multi-scale image analysis.

Key Features

Covers multiple optic flow computation classes including gradient-based differential methods, phase-based frequency domain techniques, and correlation-based area methods.

Features implementations written in Mathematica for reproducible multi-scale computer vision theory and applications.

Part of the Computational Imaging and Vision series (volume 27) from Springer, a trusted academic publisher.

Addresses dense optic flow field calculation using multi-scale differential approaches originally proposed by Florack and Nielsen.

Suitable for researchers and professionals in machine learning, artificial intelligence, and advanced image processing applications.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 September 2003
Listed Since
09 December 2006

Barcode

No barcode data available

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