Statistical Optimization for Geometric Computation: Theory and Practice - Kenichi Kanatani
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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.
Aprašymas
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.
Vairāk informācijas
| Autors | Kenichi Kanatani |
|---|---|
| Izdevējs | Dover Publications |
| Izlaides gads | 2005 |
| Vāka tips | Mīkstais vāks |
| EAN | 9780486443089 |