There has been and is a tremendous amount of research on the topic of ray tracing, spurred by the relatively recent advent of real-time ray tracing and the inevitable appearance of consumer hardware capable of handling this rendering algorithm. Besides researchers, the prospect of a brave new world attracts hobbyists (such as demo coders) and game developers: Ray tracing promises an elegant and fascinating alternative to z-buffer approaches, as well as more intuitive graphics and games development. This article provides a view from the inside on ray tracing in games and demos, where the emphasis is on performance and shortterm practical usability. It covers the way science is applied, the unique contribution of these developers to the field and their link with the research community.The Arauna ray tracer, developed at the NHTV university of applied science, is used as an example of a ray tracer that has been specifically build with games and performance in mind. Its purpose and architecture, as well as some implementation details are presented. BioJacco Bikker is a lecturer for the International Architecture and Design course of the University of Applied Sciences, Breda, The Netherlands. Before that, he worked in the Dutch game industry for ten years, for companies such as Lost Boys Interactive, Davilex, Overloaded PocketMedia and Woedend! Games. Besides his job, he wrote articles on topics such as ray tracing, rasterization, visibility determination, artificial intelligence and game development for developer websites such as Flipcode.com and Gamasutra.

The phrase "Ray tracing is the future and ever will be", as coined by David Kirk (NVIDIA fellow and former Chief Scientist), allows for two interpretations: Either, it will never be feasible, or it will be a disruptive technology.In order to show how close the state of the art is to the latter, presenters from industry will highlight the enabling technical aspects as well as the current challenges and opportunities of ray tracing. *

In this paper, we investigate the efficiency of ray queries on the CPU in the context of path tracing, where ray distributions are mostly random. We show that existing schemes that exploit data locality to improve ray tracing efficiency fail to do so beyond the first diffuse bounce, and analyze the cause for this. We then present an alternative scheme inspired by the work of Pharr et al. in which we improve data locality by using a data‐centric breadth‐first approach. We show that our scheme improves on state‐of‐the‐art performance for ray distributions in a path tracer.

We present an algorithm for generating procedural displacement maps for wrinkle patterns measured from photographs or scans. These displacement maps can contain wrinkle patterns that appear at the meso-and microscale, and are modeled using several spatially varying parameters such as the size, shape and distribution of each individual skin wrinkle. We present an algorithm to measure the parameters of skin wrinkle patterns, and show how to adapt the measured parameters to generate displacement maps with similar properties for 3D models other than the one measured. Lastly, we evaluate the quality of the generated maps by comparing them to maps acquired by scanning human skin.

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