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The non-invasive prospection of our archaeological heritage is one of the main tasks of modern archaeology and often provides the necessary bases for further activities, such as special protection or intensified research. Geophysical prospections using ground-penetrating radar (GPR) are an invaluable tool for the non-destructive exploration of archaeological monuments still buried in the ground. However, the analysis and interpretation of the data sets generated in this way is a time-consuming and complex process and requires not only three-dimensional imagination but also a broad understanding of the archaeological remains. Therefore, understandable 3D visualisations are in great demand. This paper presents a novel integrated visualisation approach, which supports conjoint visualisation of scenes composed of heterogeneous data including GPR volumes and 3D models of interpretations and reconstructions. Visual depiction of relevant dataset areas and archaeological structures is facilitated based on flexible and localised visualisation techniques. Furthermore, the rendering system supports the computation of dynamic label layouts for scenes annotations., Eurographics Workshop on Graphics and Cultural Heritage, Virtual Archaeology, 231, 234, Alexander Bornik, Mario Wallner, Alois Hinterleitner, Geert Verhoeven, and Wolfgang Neubauer, CCS Concepts: Applied computing --> Archaeology; Human-centered computing --> Scientific visualization; Geographic visualization; Computing methodologies --> Image processing

The quality of a 3D volume visualization heavily depends on a representative transfer function which is responsible for mapping the original density values to color and opacity. Finding a suitable transfer function is often a tedious task if done manually in a trial-and-error fashion by specifying piecewise linear functions for each color and opacity channel. Contrary, image-based models exploring features like gradient magnitude, histogram, or edge detection do not consider much user interaction as performed almost autonomously. Hence, we propose a new paradigm which integrates the user into the transfer function specification process. This allows an intuitive specification within an Augmented Reality environment by providing different predefined shape functions which can easily be adjusted. Moreover, a new approach is introduced which utilizes spatial information as an additional transfer function. This opens a completely new way of exploration in volume visualization.