Statistical Optimization for Geometric Computation: Theory and Practice
Автор:
Kenichi Kanatani, 528 стр., издатель:
"Dover Publications", ISBN:
0486443086
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. 1996 edition.
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