Statistical Optimization for Geometric Computation: Theory and Practice - Kenichi Kanatani
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Toimitus 22-28 arkipäivässä
30 päivän palautusoikeus
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.
Kuvaus
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.
Lisätietoja
| Kirjoittaja | Kenichi Kanatani |
|---|---|
| Julkaisija | Dover Publications |
| Julkaisuvuosi | 2005 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9780486443089 |