Motion Parameter Estimation from Optical Flow without Nuisance Parameters
نویسنده
چکیده
Many kinds of computer vision problems can be formalized as statistical estimation problems with nuisance parameters. In the past, such problems have been solved without making any distinction between the nuisance parameters and structural ones. However, a theory of statistics suggests that eliminating the nuisance parameters by assuming a probability distribution on them improves estimation accuracy of the structural parameters. In this paper, we apply this strategy to problem of estimating motion parameters from optical flow, which is a typical computer vision problem, and compare the estimation accuracy with that obtained by the conventional estimation method.
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