March 3, 2000

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Publications on the Visualization of Surface Shape :

• Victoria Interrante et al. :
  • Illustrating Surface Shape in Volume Data via Principal Direction-Driven 3D Line Integral Convolution, 1997.
  • Conveying the 3D Shape of Smoothly Curving Transparent Surfaces via Texture, 1997.
  • Enhancing Transparent Skin Surfaces with Ridge and Valley Lines, 1995.
• Alan P. Mangan & Ross T. Whitaker:
  • Partitioning 3D Surface Meshes Using Watershed Segmentation, 1999.

BibTeX references.

Online paper.

This paper describes how the set of principal directions and principal curvatures can be understood to define a natural "flow" over the surface of an object and, as such, can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape in a perceptually intuitive way.

The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures.

This paper describes how, by advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate a single scan-converted solid stroke texture that can be used to illustrate the essential shape information of any level surface in the data.

By redefining the length of the filter kernel according to the magnitude of the maximum principal curvature of the level surface at each point around which the convolution is applied, one can generate longer strokes over the more highly curved areas, where the directional information is both most stable and most relevant, and at the same time downplay the visual impact of the directional information indicated by the stroke texture in the flatter regions.

In a voxel-based approach such as this one, stroke narrowness will be constrained by the resolution of the volume within which the texture is represented. However, by adaptively indexing into multiple pre-computed texture volumes, obtained by advecting particles of increasing sizes, one may selectively widen the strokes at any point by a variable amount, determined at the time of rendering, to reflect shading information or any other function defined over the volume data.

Online paper.

Transparency can be a useful device for depicting multiple overlapping surfaces in a single image. The challenge is to render the transparent surfaces in such a way that their three-dimensional shape can be readily understood and their depth distance from underlying structures clearly perceived. This paper describes our investigations into the use of sparsely-distributed discrete, opaque texture as an "artistic device" for more explicitly indicating the relative depth of a transparent surface and for communicating the essential features of its 3D shape in an intuitively meaningful and minimally occluding way. The driving application for this work is the visualization of layered surfaces in radiation therapy treatment planning data, and the technique is illustrated on transparent isointensity surfaces of radiation dose.

We describe the perceptual motivation and artistic inspiration for defining a stroke texture that is locally oriented in the direction of greatest normal curvature (and in which individual strokes are of a length proportional to the magnitude of the curvature in the direction they indicate), and discuss two alternative methods for applying this texture to isointensity surfaces defined in a volume.

We propose an experimental paradigm for objectively measuring observers' ability to judge the shape and depth of a layered transparent surface, in the course of a task relevant to the needs of radiotherapy treatment planning, and use this paradigm to evaluate the practical effectiveness of our approach through a controlled observer experiment based on images generated from actual clinical data.

There are many applications that can benefit from the simultaneous display of multiple layers of data. The objective in these cases is to render the layered surfaces in such a way that the outer structures can be seen and seen through at the same time. This paper focuses on the particular application of radiation therapy treatment planning, in which physicians need to understand the three-dimensional distribution of radiation dose in the context of patient anatomy.

We describe a promising technique for communicating the shape and position of the transparent skin surface while at the same time minimally occluding underlying isointensity dose surfaces and anatomical objects: adding a sparse, opaque texture comprised of a small set of carefully-chosen lines. We explain the perceptual motivation for explicitly drawing ridge and valley curves on a transparent surface, describe straightforward mathematical techniques for detecting and rendering these lines, and propose a small number of reasonably effective methods for selectively emphasizing the most perceptually relevant lines in the display.

This paper describes a method for partitioning 3D surface meshes into useful segments. The proposed method generalizes morphological watersheds, an image segmentation technique, to 3D surfaces. This surface segmentation uses the total curvature of the surface as an indication of region boundaries. The surface is segmented into patches, where each patch has a relatively consistent curvature throughout, and is bounded by areas of higher, or drastically different, curvature. This algorithm has applications for a variety of important problems in visualization and geometrical modeling including 3D feature extraction, mesh reduction, texture mapping 3D surfaces, and computer aided design.

Index Terms: Surfaces, surface segmentation, watershed algorithm, curvature-based methods.

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Page created & maintained by Frederic Leymarie, 2000.
Comments, suggestions, etc., mail to: leymarie@lems.brown.edu