Triangulation of a given set of points in a plane is one of the most commonly solved problems in computer graphics and computational geometry. Because they are useful in many applications, triangulations must provide well-shaped triangles. Many criteria have been developed to provide such meshes, namely weight and angular criteria. Each criterion has its pros and cons, some of them are difficult to compute, and sometimes even the polynomial algorithm is not known. By any of the existing deterministic methods, it is not possible to compute a triangulation which satisfies more than one criterion or which contains parts developed according to several criteria. We explain how such a mixture can be generated using genetic optimization.

Figure 1: Realism in the advertising industry which combines high dynamic range images with a highly detailed CAD model of the Porsche including BRDFs of the material properties. AbstractRealism in real-time has long been a "holy grail" of the computer graphics community. While real-time performance is typically accepted as 25fps and above, the definition of realism remains less clear. If we were able to simulate the physics of the real world to minute detail then it would be possible for us to achieve images which were physically correct. However, the amount of computation required for such physical accuracy of complex scenes precludes any possibility of achieving such images in reasonable, let alone real-time, on a desktop computer for many years to come. Furthermore, there is no guarantee of realism as these images do not take into account how the human may perceive this information. Our perception of an environment is not only what we see, but may be significantly influenced by other sensory input, including sound, smell, touch, and even taste. If virtual environments are ever to be regularly used as a valuable tool to experiment in the virtual world with confidence that the results are the same as would be experienced in the real world, then we need to be able to compute these environments to be perceptually equivalent as if we were "there" in the real world; so called "there-reality" or real virtuality. This paper surveys promising efforts to date and identifies and discusses future research directions.

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In the digital heritage field, the accurate reproduction of hard-to-photograph items, such as daguerreotypes, ambrotypes, and tintypes, is an ongoing challenge. Industrial contactless sensors offer the potential to improve the quality of scanned images, but their capabilities and limitations have not been fully explored. In our research, a dataset of 48 scans was created using the hi-tech industrial contactless sensor CRUSE. Moreover, 3 rare original photographs were scanned in 16 different modes, the most suitable images were determined by specialists in the restoration, and validated through experiments involving eye-tracking, multiple computer vision, and image processing methods. Our study identified the Cruse scanning modes, which can be utilized to achieve the most accurate digital representation of scanned originals. Secondly, we proposed several methods for highlighting the degradation and minor scratches on photographs that otherwise might not be detected by the restorer’s naked eye. Our findings belong to four overlapping areas, i.e., image understanding, digital heritage, information visualization, and industrial sensors research. We publish the entire dataset under the CC BY-NC 4.0 license. The CRUSE sensor shows promise as a tool for improving the quality of scanned images of difficult-to-photograph items. Further research is necessary to fully understand its capabilities and limitations in this context.

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