EG 2015 - STARs

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https://diglib.eg.org/handle/10.2312/12147

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EUROGRAPHICS 2015: State of the Art Reports Frontmatter
(Eurographics Association, 2015) Kai Hormann; Oliver Staadt;
Morse Complexes for Shape Segmentation and Homological Analysis: Discrete Models and Algorithms
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Floriani, Leila De; Fugacci, Ulderico; Iuricich, Federico; Magillo, Paola; K. Hormann and O. Staadt
Morse theory offers a natural and mathematically-sound tool for shape analysis and understanding. It allows studying the behavior of a scalar field defined on a manifold. Starting from a Morse function, we can decompose the domain of the function into meaningful regions associated with the critical points of the field. Such decompositions, called Morse complexes, provide a segmentation of a shape and are extensively used in terrain modeling and in scientific visualization. Discrete Morse theory, a combinatorial counterpart of smooth Morse theory defined over cell complexes, provides an excellent basis for computing Morse complexes in a robust and efficient way. Moreover, since a discrete Morse complex computed over a given complex has the same homology as the original one, but fewer cells, discrete Morse theory is a fundamental tool for detecting holes efficiently in shapes through homology and persistent homology. In this survey, we review, classify and analyze algorithms for computing and simplifying Morse complexes in the context of such applications with an emphasis on discrete Morse theory and on algorithms based on it.
Photorealistic Rendering of Mixed Reality Scenes
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kronander, Joel; Banterle, Francesco; Gardner, Andrew; Miandji, Ehsan; Unger, Jonas; K. Hormann and O. Staadt
Photo-realistic rendering of virtual objects into real scenes is one of the most important research prob- lems in computer graphics. Methods for capture and rendering of mixed reality scenes are driven by a large number of applications, ranging from augmented reality to visual e ects and product visualization. Recent developments in computer graphics, computer vision, and imaging technology have enabled a wide range of new mixed reality techniques including methods for advanced image based lighting, cap- turing spatially varying lighting conditions, and algorithms for seamlessly rendering virtual objects directly into photographs without explicit measurements of the scene lighting. This report gives an overview of the state-of-the-art in this eld, and presents a categorization and comparison of current methods. Our in-depth survey provides a tool for understanding the advantages and disadvantages of each method, and gives an overview of which technique is best suited to a speci c problem.
Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Zwicker, Matthias; Jarosz, Wojciech; Lehtinen, Jaakko; Moon, Bochang; Ramamoorthi, Ravi; Rousselle, Fabrice; Sen, Pradeep; Soler, Cyril; Yoon, Sungeui E.; K. Hormann and O. Staadt
Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.
Recent Advances in Facial Appearance Capture
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Klehm, Oliver; Rousselle, Fabrice; Papas, Marios; Bradley, Derek; Hery, Christophe; Bickel, Bernd; Jarosz, Wojciech; Beeler, Thabo; K. Hormann and O. Staadt
Facial appearance capture is now firmly established within academic research and used extensively across various application domains, perhaps most prominently in the entertainment industry through the design of virtual characters in video games and films. While significant progress has occurred over the last two decades, no single survey currently exists that discusses the similarities, differences, and practical considerations of the available appearance capture techniques as applied to human faces. A central difficulty of facial appearance capture is the way light interacts with skin-which has a complex multi-layered structure-and the interactions that occur below the skin surface can, by definition, only be observed indirectly. In this report, we distinguish between two broad strategies for dealing with this complexity. “Image-based methods” try to exhaustively capture the exact face appearance under different lighting and viewing conditions, and then render the face through weighted image combinations. “Parametric methods” instead fit the captured reflectance data to some parametric appearance model used during rendering, allowing for a more lightweight and flexible representation but at the cost of potentially increased rendering complexity or inexact reproduction. The goal of this report is to provide an overview that can guide practitioners and researchers in assessing the tradeoffs between current approaches and identifying directions for future advances in facial appearance capture.
State of the Art in Hand and Finger Modeling and Animation
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Wheatland, Nkenge; Wang, Yingying; Song, Huaguang; Neff, Michael; Zordan, Victor; Jörg, Sophie; K. Hormann and O. Staadt
The human hand is a complex biological system able to perform numerous tasks with impressive accuracy and dexterity. Gestures furthermore play an important role in our daily interactions, and humans are particularly skilled at perceiving and interpreting detailed signals in communications. Creating believable hand motions for virtual characters is an important and challenging task. Many new methods have been proposed in the Computer Graphics community within the last years, and significant progress has been made towards creating convincing, detailed hand and finger motions. This state of the art report presents a review of the research in the area of hand and finger modeling and animation. Starting with the biological structure of the hand and its implications for how the hand moves, we discuss current methods in motion capturing hands, data-driven and physics-based algorithms to synthesize their motions, and techniques to make the appearance of the hand model surface more realistic. We then focus on areas in which detailed hand motions are crucial, such as manipulation and communication. Our report concludes by describing emerging trends and applications for virtual hand animation.
The State of the Art in HDR Deghosting: A Survey and Evaluation
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Tursun, Okan Tarhan; Akyüz, Ahmet Oğuz; Erdem, Aykut; Erdem, Erkut; K. Hormann and O. Staadt
Obtaining a high quality high dynamic range (HDR) image in the presence of camera and object movement has been a long-standing challenge. Many methods, known as HDR deghosting algorithms, have been developed over the past ten years to undertake this challenge. Each of these algorithms approaches the deghosting problem from a different perspective, providing solutions with different degrees of complexity, solutions that range from rudimentary heuristics to advanced computer vision techniques. The proposed solutions generally differ in two ways: (1) how to detect ghost regions and (2) what to do to eliminate ghosts. Some algorithms choose to completely discard moving objects giving rise to HDR images which only contain the static regions. Some other algorithms try to find the best image to use for each dynamic region. Yet others try to register moving objects from different images in the spirit of maximizing dynamic range in dynamic regions. Furthermore, each algorithm may introduce different types of artifacts as they aim to eliminate ghosts. These artifacts may come in the form of noise, broken objects, under- and over-exposed regions, and residual ghosting. Given the high volume of studies conducted in this field over the recent years, a comprehensive survey of the state of the art is required. Thus, the first goal of this paper is to provide this survey. Secondly, the large number of algorithms brings about the need to classify them. Thus the second goal of this paper is to propose a taxonomy of deghosting algorithms which can be used to group existing and future algorithms into meaningful classes. Thirdly, the existence of a large number of algorithms brings about the need to evaluate their effectiveness, as each new algorithm claims to outperform its precedents. Therefore, the last goal of this paper is to share the results of a subjective experiment which aims to evaluate various state-of-the-art deghosting algorithms.

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