Statistical Optimization for Geometric Computation

Statistical Optimization for Geometric Computation
Author :
Publisher : Courier Corporation
Total Pages : 548
Release :
ISBN-10 : 9780486443089
ISBN-13 : 0486443086
Rating : 4/5 (086 Downloads)

Book Synopsis Statistical Optimization for Geometric Computation by : Kenichi Kanatani

Download or read book Statistical Optimization for Geometric Computation written by Kenichi Kanatani and published by Courier Corporation. This book was released on 2005-07-26 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 sensors. The 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.


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