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Erschienen in:
1989 | OriginalPaper | Buchkapitel
Conclusions
verfasst von : Richard Szeliski
Erschienen in: Bayesian Modeling of Uncertainty in Low-Level Vision
Verlag: Springer US
Enthalten in: Professional Book Archive
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In this book, we have developed a Bayesian model for the dense fields that arise in low-level vision, and shown how this model can be be applied to a number of low-level vision problems. We have used this model to analyze the assumptions inherent in existing vision algorithms, to improve the performance of these algorithms, and to devise novel algorithms for problems which have not previously been studied. In this chapter, we will summarize these important results and discuss how they can be extended in the future to other computer vision problems.