The haloed line effect for hidden line elimination.

In this paper we present a pipeline for rendering dynamic 2D/3D line drawings efficiently. Our main goal is to create efficient static renditions and coherent animations of line drawings in a setting where lines can be added, deleted and arbitrarily transformed on-the-fly. Such a dynamic setting enables us to handle interactively sketched 2D line data, as well as arbitrarily transformed 3D line data in a unified manner. We evaluate the proximity of screen projected strokes to simplify them while preserving their continuity. We achieve this by using a special data structure that facilitates efficient proximity calculations in a dynamic setting. This on-the-fly proximity evaluation also facilitates generation of appropriate visibility cues to mitigate depth ambiguities and visual clutter for 3D line data. As we perform all these operations using only line data, we can create line drawings from 3D models without any surface information. We demonstrate the effectiveness and applicability of our approach by showing several examples with initial line representations obtained from a variety of sources: 2D and 3D hand-drawn sketches and 3D salient geometry lines obtained from 3D surface representations.

Section: Visibility Cuesmentioning

confidence: 96%

Efficient and Dynamic Simplification of Line Drawings

Shesh

Chen

2008

“…Another important style element in NPR is the use of halos [ARS79,Elb95] which can greatly enhance depth perception [TCM06, BG07, EBRI09]. We use halos, in particular, to separate focus objects from the background.…”

Section: Non-photorealistic Renderingmentioning

confidence: 99%

DTI in Context: Illustrating Brain Fiber Tracts In Situ

Svetachov

Everts

Isenberg

2010

We present an interactive illustrative visualization method inspired by traditional pen-and-ink illustration styles. Specifically, we explore how to provide context around DTI fiber tracts in the form of surfaces of the brain, the skull, or other objects such as tumors. These contextual surfaces are derived from either segmentation data or generated using interactive iso-surface extraction and are rendered with a flexible, slice-based hatching technique, controlled with ambient occlusion. This technique allows us to produce a consistent and frame-coherent appearance with precise control over the lines. In addition, we provide context through cutting planes onto which we render gray matter with stippling. Together, our methods not only facilitate the interactive exploration and illustration of brain fibers within their anatomical context but also allow us to produce high-quality images for print reproduction. We provide evidence for the success of our approach with an informal evaluation with domain experts.

“…To enhance the visualization of line primitives several techniques have been proposed. Halo based methods for lines were first presented by Appel et al [ARS79]. These techniques give better depth perception.…”

Section: Related Workmentioning

confidence: 99%

Illustrative White Matter Fiber Bundles

Otten¹,

Vilanova²,

Wetering³

2010

Diffusion Tensor Imaging (DTI) has made feasible the visualization of the fibrous structure of the brain white matter. In the last decades, several fiber-tracking methods have been developed to reconstruct the fiber tracts from DTI data. Usually these fiber tracts are shown individually based on some selection criteria like region of interest. However, if the white matter as a whole is being visualized clutter is generated by directly rendering the individual fiber tracts. Often users are actually interested in fiber bundles, anatomically meaningful entities that abstract from the fibers they contain. Several clustering techniques have been developed that try to group the fiber tracts in fiber bundles. However, even if clustering succeeds, the complex nature of white matter still makes it difficult to investigate. In this paper, we propose the use of illustration techniques to ease the exploration of white matter clusters. We create a technique to visualize an individual cluster as a whole. The amount of fibers visualized for the cluster is reduced to just a few hint lines, and silhouette and contours are used to improve the definition of the cluster borders. Multiple clusters can be easily visualized by a combination of the single cluster visualizations. Focus+context concepts are used to extend the multiple-cluster renderings. Exploded views ease the exploration of the focus cluster while keeping the context clusters in an abstract form. Real-time results are achieved by the GPU implementation of the presented techniques.