Gisela Klette

A system for articulated tracking incorporating a clothing model

In this paper an approach for motion capture of dressed people is presented. A cloth draping method is incorporated in a silhouette based motion capture system. This leads to a simultaneous estimation of pose, joint angles, cloth draping parameters and wind forces. An error functional is formalized to minimize the involved parameters simultaneously. This allows for reconstruction of the underlying kinematic structure, even though it is covered with fabrics. Finally, a quantitative error analysis is performed. Pose results are compared with results obtained from a commercially available marker based tracking system. The deviations have a magnitude of three degrees which indicates a reasonably stable approach.

3D topological thinning by identifying non-simple voxels

Topological thinning includes tests for voxels to be simple or not. A point (pixel or voxel) is simple if the change of its image value does not change the topology of the image. A problem with topology preservation in 3D is that checking voxels to be simple is more complex and time consuming than in 2D. In this paper, we review some characterizations of simple voxels and we propose a new methodology for identifying non-simple points. We implemented our approach by modifying an existing 3D thinning algorithm and achieved an improved running time.

Branch voxels and junctions in 3d skeletons

Branch indices of points on curves (introduced by Urysohn and Menger) are of basic importance in the mathematical theory of curves, defined in Euclidean space. This paper applies the concept of branch points in the 3D orthogonal grid, motivated by the need to analyze curve-like structures in digital images. These curve-like structures have been derived as 3D skeletons (by means of thinning). This paper discusses approaches of defining branch indices for voxels on 3D skeletons, where the notion of a junction will play a crucial role. We illustrate the potentials of using junctions in 3D image analysis based on a recent project of analyzing the distribution of astrocytes in human brain tissue.

Simple Points in 2D and 3D Binary Images

The notion of a simple point is of fundamental importance for deformations of digital images. A point (pixel or voxel) is simple if the change of its value does not change the topology of the image. This article unifies characterizations of simple points. It shows equivalences of characterizations based on different models that are useful for the design of deformation algorithms (thinning and magnification). The paper also specifies an algorithm for identifying simple voxels.

RealText-lex: A Lexicalization Framework for RDF Triples

Abstract The online era has made available almost cosmic amounts of information in the public and semi-restricted domains, prompting development of corresponding host of technologies to organize and navigate this information. One of these developing technologies deals with encoding information from free form natural language into a structured form as RDF triples. This representation enables machine processing of the data, however the processed information can not be directly converted back to human language. This has created a need to be able to lexicalize machine processed data existing as triples into a natural language, so that there is seamless transition between machine representation of information and information meant for human consumption. This paper presents a framework to lexicalize RDF triples extracted from DBpedia, a central interlinking hub for the emerging Web of Data. The framework comprises of four pattern mining modules which generate lexicalization patterns to transform triples to natural language sentences. Among these modules, three are based on lexicons and the other works on extracting relations by exploiting unstructured text to generate lexicalization patterns. A linguistic accuracy evaluation and a human evaluation on a sub-sample showed that the framework can produce patterns which are accurate and emanate human generated qualities.

A Tweet Classification Model Based on Dynamic and Static Component Topic Vectors

This paper presents an unsupervised architecture for retrieving and ranking conceptually related tweets which can be used in real time. We present a model for ranking tweets with respect to topic relevance in order to improve the accuracy of information extraction.

Digital Convexity and Cavity Trees

The notion convexity has a long history in mathematics. It is a useful concept to describe shapes, functions, smoothness of curves or boundaries, and it has applications in many fields. Researchers apply different definitions for digital convexity to adapt known concepts from the continuous space, and to make use of proven theories and results. We review different approaches and we propose cavity trees for a analyzing the convexity of digital objects, b to decompose those objects into meaningful parts, and c to show an easy way to find convex and concave parts of a boundary of a digital region.