EG 2018 - STARs (CGF 37-2)

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https://diglib.eg.org/handle/10.2312/2632163

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Browsing EG 2018 - STARs (CGF 37-2) by Subject "Reconstruction"

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    State of the Art on 3D Reconstruction with RGB-D Cameras
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Zollhöfer, Michael; Stotko, Patrick; Görlitz, Andreas; Theobalt, Christian; Nießner, Matthias; Klein, Reinhard; Kolb, Andreas; Hildebrandt, Klaus and Theobalt, Christian
    The advent of affordable consumer grade RGB-D cameras has brought about a profound advancement of visual scene reconstruction methods. Both computer graphics and computer vision researchers spend significant effort to develop entirely new algorithms to capture comprehensive shape models of static and dynamic scenes with RGB-D cameras. This led to significant advances of the state of the art along several dimensions. Some methods achieve very high reconstruction detail, despite limited sensor resolution. Others even achieve real-time performance, yet possibly at lower quality. New concepts were developed to capture scenes at larger spatial and temporal extent. Other recent algorithms flank shape reconstruction with concurrent material and lighting estimation, even in general scenes and unconstrained conditions. In this state-of-the-art report, we analyze these recent developments in RGB-D scene reconstruction in detail and review essential related work. We explain, compare, and critically analyze the common underlying algorithmic concepts that enabled these recent advancements. Furthermore, we show how algorithms are designed to best exploit the benefits of RGB-D data while suppressing their often non-trivial data distortions. In addition, this report identifies and discusses important open research questions and suggests relevant directions for future work.
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    State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Zollhöfer, Michael; Thies, Justus; Garrido, Pablo; Bradley, Derek; Beeler, Thabo; Pérez, Patrick; Stamminger, Marc; Nießner, Matthias; Theobalt, Christian; Hildebrandt, Klaus and Theobalt, Christian
    The computer graphics and vision communities have dedicated long standing efforts in building computerized tools for reconstructing, tracking, and analyzing human faces based on visual input. Over the past years rapid progress has been made, which led to novel and powerful algorithms that obtain impressive results even in the very challenging case of reconstruction from a single RGB or RGB-D camera. The range of applications is vast and steadily growing as these technologies are further improving in speed, accuracy, and ease of use. Motivated by this rapid progress, this state-of-the-art report summarizes recent trends in monocular facial performance capture and discusses its applications, which range from performance-based animation to real-time facial reenactment. We focus our discussion on methods where the central task is to recover and track a three dimensional model of the human face using optimization-based reconstruction algorithms. We provide an in-depth overview of the underlying concepts of real-world image formation, and we discuss common assumptions and simplifications that make these algorithms practical. In addition, we extensively cover the priors that are used to better constrain the under-constrained monocular reconstruction problem, and discuss the optimization techniques that are employed to recover dense, photo-geometric 3D face models from monocular 2D data. Finally, we discuss a variety of use cases for the reviewed algorithms in the context of motion capture, facial animation, as well as image and video editing.