Realistic hair modeling is a fundamental part of creating virtual humans in computer graphics. This paper surveys the state of the art in the major topics of hair modeling: hairstyling, hair simulation, and hair rendering. Because of the difficult, often unsolved problems that arise in alt these areas, a broad diversity of approaches is used, each with strengths that make it appropriate for particular applications. We discuss each of these major topics in turn, presenting the unique challenges facing each area and describing solutions that have been presented over the years to handle these complex issues. Finally, we outline some of the remaining computational challenges in hair modeling

/pdf/a-survey-on-hair-modeling-styling-simulation-and-rendering-1sdf5kj627.pdf

A Survey on Hair Modeling: Styling, Simulation, and Rendering

The computation of high-fidelity images in real-time remains one of the key challenges for computer graphics Recent work has shown that by understanding the human visual system, selective rendering may be used to render only those parts to which the human viewer is attending at high quality and the rest of the scene at a much lower quality This can result in a significant reduction in computational time, without the viewer being aware of the quality difference Selective rendering is guided by models of the human visual system, typically in the form of a 2D saliency map, which predict where the user will be looking in any scene Computation of these maps themselves often take many seconds, thus precluding such an approach in any interactive system, where many frames need to be rendered per second In this paper we present a novel saliency map which exploits the computational performance of modern GPUs With our approach it is thus possible to calculate this map in milliseconds, allowing it to be part of a real time rendering system In addition, we also show how depth, habituation and motion can be added to the saliency map to further guide the selective rendering This ensures that only the most perceptually important parts of any animated sequence need be rendered in high quality The rest of the animation can be rendered at a significantly lower quality, and thus much lower computational cost, without the user being aware of this difference

A GPU based saliency map for high-fidelity selective rendering

Tone-mapping constitutes a key component within the field of high dynamic range HDR imaging. Its importance is manifested in the vast amount of tone-mapping methods that can be found in the literature, which are the result of an active development in the area for more than two decades. Although these can accommodate most requirements for display of HDR images, new challenges arose with the advent of HDR video, calling for additional considerations in the design of tone-mapping operators TMOs. Today, a range of TMOs exist that do support video material. We are now reaching a point where most camera captured HDR videos can be prepared in high quality without visible artifacts, for the constraints of a standard display device. In this report, we set out to summarize and categorize the research in tone-mapping as of today, distilling the most important trends and characteristics of the tone reproduction pipeline. While this gives a wide overview over the area, we then specifically focus on tone-mapping of HDR video and the problems this medium entails. First, we formulate the major challenges a video TMO needs to address. Then, we provide a description and categorization of each of the existing video TMOs. Finally, by constructing a set of quantitative measures, we evaluate the performance of a number of the operators, in order to give a hint on which can be expected to render the least amount of artifacts. This serves as a comprehensive reference, categorization and comparative assessment of the state-of-the-art in tone-mapping for HDR video.

/pdf/a-comparative-review-of-tone-mapping-algorithms-for-high-5dalfie38i.pdf

A comparative review of tone-mapping algorithms for high dynamic range video

Populated virtual urban environments are important in many applications, from urban planning to entertainment. At the current stage of technology, users can interactively navigate through complex, polygon-based scenes rendered with sophisticated lighting effects and high-quality antialiasing techniques. As a result, animated characters (or agents) that users can interact with are also becoming increasingly common. However, rendering crowded scenes with thousands of different animated virtual people in real time is still challenging. To address this, we developed an image-based rendering approach for displaying multiple avatars. We take advantage of the properties of the urban environment and the way a viewer and the avatars move within it to produce fast rendering, based on positional and directional discretization. To display many different individual people at interactive frame rates, we combined texture compression with multipass rendering.

/pdf/image-based-crowd-rendering-n3p8lxwr4m.pdf

Image-based crowd rendering

Virtual reconstruction and representation of historical environments and objects have been of research interest for nearly two decades. Physically based and historically accurate illumination allows archaeologists and historians to authentically visualise a past environment to deduce new knowledge. This report reviews the current state of illuminating cultural heritage sites and objects using computer graphics for scientific, preservation and research purposes. We present the most noteworthy and up-to-date examples of reconstructions employing appropriate illumination models in object and image space, and in the visual perception domain. Finally, we also discuss the difficulties in rendering, documentation, validation and identify probable research challenges for the future. The report is aimed for researchers new to cultural heritage reconstruction who wish to learn about methods to illuminate the past.

Illuminating the past: state of the art

Rendering Techniques

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