One of the most important elements needed for effective training in Virtual Reality (VR) is the generation of variable scenarios. Without this, trainees quickly become familiar with a scene and the natural variations encountered in real-life situations cannot be reproduced. Generating such models in VR-based applications is difficult, but with the increase in computational power (allowing for larger and more finely-detailed virtual environments) there is an increasing demand for improved methods for model acquisition, enhancement, optimization and adaptation.

The field of medicine lends itself very well to VR-based training particularly in the area of surgery. In this book Matthias Harders examines the main components needed when defining effective scenarios: