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Statistical Optimization for Geometric Computation - (Dover Books on Mathematics) by Kenichi Kanatani (Paperback)
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About this item
Highlights
- 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.
- Author(s): Kenichi Kanatani
- 528 Pages
- Computers + Internet, Optical Data Processing
- Series Name: Dover Books on Mathematics
Description
Book Synopsis
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.Dimensions (Overall): 8.4 Inches (H) x 5.4 Inches (W) x 1.1 Inches (D)
Weight: 1.2 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 528
Series Title: Dover Books on Mathematics
Genre: Computers + Internet
Sub-Genre: Optical Data Processing
Publisher: Dover Publications
Format: Paperback
Author: Kenichi Kanatani
Language: English
Street Date: July 26, 2005
TCIN: 85173410
UPC: 9780486443089
Item Number (DPCI): 247-61-6111
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 1.1 inches length x 5.4 inches width x 8.4 inches height
Estimated ship weight: 1.2 pounds
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