In this paper, we present a semi-automatic approach to efficiently and robustly recover the characteristic feature curves of a given free-form surface. The technique supports a sketch-based interface where the user just has to roughly sketch the location of a feature by drawing a stroke directly on the input mesh. The system then snaps this initial curve to the correct position based on a graph-cut optimization scheme that takes various surface properties into account. Additional position constraints can be placed and modified manually which allows for an interactive feature curve editing functionality. We demonstrate the usefulness of our technique by applying it to a practical problem scenario in reverse engineering. Here, we consider the problem of generating a statistical (PCA) shape model for car bodies. The crucial step is to establish proper feature correspondences between a large number of input models. Due to the significant shape variation, fully automatic techniques are doomed to failure. With our simple and effective feature curve recovery tool, we can quickly sketch a set of characteristic features on each input model which establishes the correspondence to a pre-defined template mesh and thus allows us to generate the shape model. Finally, we can use the feature curves and the shape model to implement an intuitive modeling metaphor to explore the shape space spanned by the input models.

New product development involves people with different backgrounds. Designers, engineers, and consumers all have different criteria, and these criteria interact. Early concepts evolve in this kind of collaborative context, and there is a need for dynamic visualization of the interaction between design shape and other shape-related design criteria. In this paper, a Morphable Model is defined from simplified representations of suitably chosen real cars, providing a continuous shape space to navigate, manipulate, and visualize. Physical properties and consumer-provided scores for the real cars (such as 'weight' and 'sportiness') are estimated for new designs across the shape space. This coupling allows one to manipulate the shape directly while reviewing the impact on estimated criteria, or conversely, to manipulate the criterial values of the current design to produce a new shape with more desirable attributes.

Within the large spectrum of possible VR application areas, automotive applications were among the first to appear, and are among the most demanding. Technology has not been sufficiently sophisticated for many tasks. The troubling thought is that we are happy to push the technology envelope, but don't really know how useful this technology is, or can be. Could I do my job even if I had a real-time, ortho-stereoscopic, head-tracked, multi-viewer, wide-field-of-view, high-dynamic-range display with eye-limiting acuity?