Statistical Optimization for Geometric Computation: Theory and Practice by Kenic

$35.84

Statistical Optimization for Geometric Computation by Kenichi Kanatani

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Format Paperback

Condition Brand New

Description This text discusses the mathematical foundations of statistical inference for building 3-dimensional models from image and sensor data that contain noise — a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. 1996 edition.

Publisher Description

This text for graduate students discusses the mathematical foundations of statistical inference for building three-dimensional models from image and sensor data that contain noise--a task involving autonomous robots guided by video cameras and text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. The numerous mathematical prerequisites for developing the theories are explained systematically in separate chapters. These methods range from linear algebra, optimization, and geometry to a detailed statistical theory of geometric patterns, fitting estimates, and model selection. In addition, examples drawn from both synthetic and real data demonstrate the insufficiencies of conventional procedures and the improvements in accuracy that result from the use of optimal methods.

Details

ISBN 0486443086
ISBN-13 9780486443089
Title Statistical Optimization for Geometric Computation
Author Kenichi Kanatani
Format Paperback
Year 2005
Pages 528
Publisher Dover Publications Inc.

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