Abstract for carr_tr300

Cambridge University Engineering Department Technical Report CUED/F-INFENG/TR300


Jonathan C. Carr

September 1997

This paper presents a technique for reconstructing objects from noisy boundary data that are scattered, unorganised and incomplete. Volume intersection algorithms are used to reconstruct incomplete objects from their silhouettes. An imagined light source is moved about the data and the cumulative amount of `light' seen at each point in space is interpreted as indicating the likelihood that the point is inside the object. The object data need not be uniformly distributed nor exclusively come from the surface of the object. Explicit identification of false object data and distinction between surface and interior data are avoided. A limitation of volume intersection algorithms is their inability to reconstruct concave surfaces. We show how the dependency of the visual hull of an object on the viewing region can be used to resolve concavities. The novel concept of a localised viewing region is introduced and shown to improve the ability of the method to reconstruct complex shapes in the presence of noise. Algorithms for 2D pixel and 3D voxel data are described and applied to 3D ultrasound data.

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