Deborah Silver

Skeleton based shape matching and retrieval

We describe a novel method for searching and comparing 3D objects. The method encodes the geometric and topological information in the form of a skeletal graph and uses graph matching techniques to match the skeletons and to compare them. The skeletal graphs can be manually annotated to refine or restructure the search. This helps in choosing between a topological similarity and a geometric (shape) similarity. A feature of skeletal matching is the ability to perform part-matching, and its inherent intuitiveness, which helps in defining the search and in visualizing the results. Also, the matching results, which are presented in a per-node basis can be used for driving a number of registration algorithms, most of which require a good initial guess to perform registration. We also describe a visualization tool to aid in the selection and specification of the matched objects.

Curve-Skeleton Properties, Applications, and Algorithms

Curve-skeletons are thinned 1D representations of 3D objects useful for many visualization tasks including virtual navigation, reduced-model formulation, visualization improvement, animation, etc. There are many algorithms in the literature describing extraction methodologies for different applications; however, it is unclear how general and robust they are. In this paper, we provide an overview of many curve-skeleton applications and compile a set of desired properties of such representations. We also give a taxonomy of methods and analyze the advantages and drawbacks of each class of algorithms.

Computing hierarchical curve-skeletons of 3D objects

A curve-skeleton of a 3D object is a stick-like figure or centerline representation of that object. It is used for diverse applications, including virtual colonoscopy and animation. In this paper, we introduce the concept of hierarchical curve-skeletons and describe a general and robust methodology that computes a family of increasingly detailed curve-skeletons. The algorithm is based upon computing a repulsive force field over a discretization of the 3D object and using topological characteristics of the resulting vector field, such as critical points and critical curves, to extract the curve-skeleton. We demonstrate this method on many different types of 3D objects (volumetric, polygonal and scattered point sets) and discuss various extensions of this approach.

Visiometrics, Juxtaposition and Modeling

With the advent of massively parallel computers, the evolution of nonlinear dynamical systems such as fluids and plasmas is being investigated in three dimensions at increasingly high resolutions. Today a typical physical volume is represented by 100 3 grid points, and we may expect the resolution to increase to 1000 3 by the end of the decade.

Visualizing features and tracking their evolution

We describe basic algorithms to extract coherent amorphous regions (features or objects) from 2 and 3D scalar and vector fields and then track them in a series of consecutive time steps. We use a combination of techniques from computer vision, image processing, computer graphics, and computational geometry and apply them to data sets from computational fluid dynamics. We demonstrate how these techniques can reduce visual clutter and provide the first step to quantifying observable phenomena. These results can be generalized to other disciplines with continuous time-dependent scalar (and vector) fields.<<ETX>>

Parameter-controlled volume thinning

The availability of large 3D datasets has made volume thinning essential for compact representation of shapes. The density of the skeletal structure resulting from the thinning process depends on the application. Current thinning techniques do not allow control over the density and can therefore address only specific applications. In this paper, we describe an algorithm which uses a thinness parameter to control the thinning process and thus the density of the skeletal structure. We present applications from CFD and medical visualization and show how the skeletal structure can be used in these domains. We also illustrate a technique for constructing a centerline for surgical navigation.

Iconic techniques for feature visualization

Presents a conceptual framework and a process model for feature extraction and iconic visualization. Feature extraction is viewed as a process of data abstraction, which can proceed in multiple stages, and corresponding data abstraction levels. The features are represented by attribute sets, which play a key role in the visualization process. Icons are symbolic parametric objects, designed as visual representations of features. The attributes are mapped to the parameters (or degrees of freedom) of an icon. We describe some generic techniques to generate attribute sets, such as volume integrals and medial axis transforms. A simple but powerful modeling language was developed to create icons, and to link the attributes to the icon parameters. We present illustrative examples of iconic visualization created with the techniques described, showing the effectiveness of this approach.

3D object retrieval using many-to-many matching of curve skeletons

We present a 3D matching framework based on a many-to-many matching algorithm that works with skeletal representations of 3D volumetric objects. We demonstrate the performance of this approach on a large database of 3D objects containing more than 1000 exemplars. The method is especially suited to matching objects with distinct part structure and is invariant to part articulation. Skeletal matching has an intuitive quality that helps in defining the search and visualizing the results. In particular, the matching algorithm produces a direct correspondence between two skeletons and their parts, which can be used for registration and juxtaposition.

A portable dextrous master with force feedback

Dextrous masters control robots and artificial environments through hand gestures. Commercial products have open-loop control, without force feedback to the operator. There is a need for portable systems that have force feedback, but are still sufficiently compact to be desktop. In this paper we discuss a prototype master providing force feedback for the Dataglove. The master structure and its actuator characteristics are presented first. Then a control model is given based on finger parameters and joint coupling. The glove calibration is subsequently discussed, taking into account the influence of the feedback structure. The experimental setup and initial results are presented last.

Feature extraction and iconic visualization

We present a conceptual framework and a process model for feature extraction and iconic visualization. The features are regions of interest extracted from a dataset. They are represented by attribute sets, which play a key role in the visualization process. These attribute sets are mapped to icons, or symbolic parametric objects, for visualization. The features provide a compact abstraction of the original data, and the icons are a natural way to visualize them. We present generic techniques to extract features and to calculate attribute sets, and describe a simple but powerful modeling language which was developed to create icons and to link the attributes to the icon parameters. We present illustrative examples of iconic visualization created with the techniques described, showing the effectiveness of this approach.