This manuscript identifies and documents unsolved problems and research challenges in the extended reality (XR) domain (i.e., virtual (VR), augmented (AR), and mixed reality (MR)). The manuscript is structured to include technology, design, and human factor perspectives. The text is visualization/display-focused, that is, other modalities such as audio, haptic, smell, and touch, while important for XR, are beyond the scope of this paper. We further narrow our focus to mainly geospatial research, with necessary deviations to other domains where these technologies are widely researched. The main objective of the study is to provide an overview of broader research challenges and directions in XR, especially in spatial sciences. Aside from the research challenges identified based on a comprehensive literature review, we provide case studies with original results from our own studies in each section as examples to demonstrate the relevance of the challenges in the current research. We believe that this paper will be of relevance to anyone who has scientific interest in extended reality, and/or uses these systems in their research.

Generalisation is well recognised as a complex process that should trigger specific algorithms, on different types of objects in some logical or appropriate order. To guide the process (where and how to generalise) one solution is to distinguish characterisation from the generalisation process. Characterisation aims at finding and describing relevant 'working areas' that can be a part of an object or a set of objects. As a result, the choice of an appropriate algorithm(s) becomes easier and can be constrained by the detected properties of this new entity. This paper presents a method to both detect and characterise building alignments in an effort to improve the use of generalisation algorithms namely typification and displacement. The first step consists of the identification of building alignments from straight-line templates. The second step characterises these alignments to retain only those that are perceptually regular. The characterisation is based on an analysis of the spatial location of buildings as well as on the properties of the buildings that belong to the alignment in question. To evaluate the regularity of the distribution, estimators are proposed for each property.. At the end a global quality estimator of the perceptual alignment-based on the aggregation of the estimators -is proposed. This global estimator is used to retain the best building alignments that will then be carefully generalised. The results presented have been implemented in the Lamps2 GIS software.

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Tactile maps are essential tools for visually impaired people to comprehend space and to support the simple pedestrian trips made difficult by their disability. Tactile maps are created manually and printed by specialists, and it takes a large amount of time to create a new one, which prevents using them on demand for everyday use. As a consequence, researchers and cartographers try to automate this creation process, but the existing automated derivation processes do not include generalization or advanced stylization steps, which limits their effectiveness. This paper reports first experiments to include such complex automated cartography processes to provide on demand tactile maps for visually impaired people. These first experiments were more intended to raise real research issues than solve them, and the paper discusses these issues in a research agenda to achieve automatically derived tactile maps.

Color palettes are widely used by artists to define colors of artworks and explore color designs. In general, artists select the colors of a palette by following a set of rules, e.g. contrast or relative luminance. Existing interactive palette exploration tools explore palette spaces following limited constraints defined as geometric configurations in color space e.g. harmony rules on the color wheel. Palette search algorithms sample palettes from color relations learned from an input dataset, however they cannot provide interactive user edits and palette refinement. We introduce in this work a new versatile formulation enabling the creation of constraint-based interactive palette exploration systems. Our technical contribution is a graph-based palette representation, from which we define palette exploration as a minimization problem that can be solved efficiently and provide real-time feedback. Based on our formulation, we introduce two interactive palette exploration strategies: constrained palette exploration, and for the first time, constrained palette interpolation. We demonstrate the performances of our approach on various application cases and evaluate how it helps users finding trade-offs between concurrent constraints.