Bayesian Modeling of Uncertainty in Low-Level Vision

Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain or inaccurate, and the problems of recovering scene information from images are often ill-posed or underconstrained. This research monograph, which is based on Richard Szeliski's Ph.D. dissertation at C...

Ausführliche Beschreibung

Bibliographische Detailangaben

1. Verfasser:	Szeliski, Richard (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Boston, MA Springer US 1989
Schriftenreihe:	The Kluwer International in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors 79
Schlagworte:	Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Computer science Artificial intelligence Computer graphics Control engineering Robotics Mechatronics Bayes-Verfahren Maschinelles Sehen
Online-Zugang:	DE-634 URL des Erstveröffentlichers
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