Paperback. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Bibliographic Details

Title: Statistical Optimization for Geometric Computation: Theory and Practice (Paperback)
Publisher: Dover Publications, New York
Publication Date: 2005
Language: English
ISBN 10: 0486443086
ISBN 13: 9780486443089
Binding: Paperback
Condition: new

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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.

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