Abstract
This paper describes a novel approach to surface tracking in volumetric image stacks. It draws on a statistical model of the uncertainties inherent in the characterisation of intensity surfaces to compute an evidential field for interframe contour displacements. This field is computed using Gaussian density kernels which are parameterised in terms of the variance-covariance matricies for contour displacement. The underlying variance model accommodates the effects of raw image noise on the estimated surface normals. The evidential field effectively couples contour displacements to the intensity features on successive frames through a statistical process of contour tracking. With the evidential field to hand, hard contours may be extracted in a decision theoretic manner.
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© 1995 Springer-Verlag Berlin Heidelberg
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Sharp, N.G., Hancock, E.R. (1995). Statistical surface tracking. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_354
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DOI: https://doi.org/10.1007/3-540-60268-2_354
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