Digital signatures provide a valuable tool for secure internet trading by ensuring data authenticity and integrity and most importantly by enforcing commitment and non-repudiation for the transacting parties. The action of digitally signing has, however, several intrinsic weaknesses that introduce syntactic and semantic distance between a signer and a relying party. As a result, digitally signe...

Obtaining high-quality 3D models of real world objects is an important task in computer vision. A very promising approach to achieve this is given by variational range image integration methods: They are able to deal with a substantial amount of noise and outliers, while regularising and thus creating smooth surfaces at the same time. Our paper extends the state-of-the-art approach of Zach et a...

Modeling appealing virtual scenes is an elaborate and time-consuming task, requiring not only training and experience, but also powerful modeling tools providing the desired functionality to the user. In this paper, we describe a modeling approach using signed distance functions as an underlying representation for objects, handling both conventional and complex surface manipulations. Scenes def...

This thesis presents a study of the signed distance function as a three-dimensional implicit surface representation and provides a detailed overview of its different properties. A method for generating such a representation using the depth-image output from a Kinect camera is reviewed in detail. In order to improve the quality of the implicit function that can be obtained, registration of multi...

1 Distance Fields Given an implicit surface ∂S with S ⊆ R the corresponding distance field (also called signed distance function) D : R → R which maps a point p from the domain of the distance field R to a real-valued distance value is obtained by distance transforming the surface using the formula D(p) = sign(p) ·min{d(p, q) : q ∈ S} (1) The metric d(p, q) used is the standard Euclidean metric...

1 Abstract We give a simple decoding algorithm to decode linear cyclic codes of odd length over the ring R = F2 + uF2 = f0; 1; u; u = u + 1g, where u 2 = 0. A spectral representation of the cyclic codes over R is given and a BCH like bound is given for the Lee distance of the codes. The ring R shares many properties of Z4 and F4 and admits a linear \Gray map". 1 0 1 u u u 0 u 1 u u 0 u u 0 + 0 ...