STARs
https://diglib.eg.org:443/handle/10.2312/272
Eurographics 2009 - STARs2024-03-28T08:19:33ZTime-of-Flight Sensors in Computer Graphics
https://diglib.eg.org:443/handle/10.2312/egst.20091064.119-134
Time-of-Flight Sensors in Computer Graphics
Kolb, Andreas; Barth, Erhardt; Koch, Reinhard; Larsen, Rasmus
M. Pauly and G. Greiner
A growing number of applications depend on accurate and fast 3D scene analysis. Examples are model and lightfield acquisition, collision prevention, mixed reality, and gesture recognition. The estimation of a range map by image analysis or laser scan techniques is still a time-consuming and expensive part of such systems. A lower-priced, fast and robust alternative for distance measurements are Time-of-Flight (ToF) cameras. Recently, significant improvements have been made in order to achieve low-cost and compact ToF-devices, that have the potential to revolutionize many fields of research, including Computer Graphics, Computer Vision and Man Machine Interaction (MMI). These technologies are starting to have an impact on research and commercial applications. The upcoming generation of ToF sensors, however, will be even more powerful and will have the potential to become "ubiquitous real-time geometry devices" for gaming, web-conferencing, and numerous other applications. This STAR gives an account of recent developments in ToF-technology and discusses the current state of the integration of this technology into various graphics-related applications.
2009-01-01T00:00:00ZState of the Art in Example-based Texture Synthesis
https://diglib.eg.org:443/handle/10.2312/egst.20091063.093-117
State of the Art in Example-based Texture Synthesis
Wie, Li-Yi; Lefebvre, Sylvain; Kwatra, Vivek; Turk, Greg
M. Pauly and G. Greiner
Recent years have witnessed significant progress in example-based texture synthesis algorithms. Given an example texture, these methods produce a larger texture that is tailored to the user s needs. In this state-of-the-art report, we aim to achieve three goals: (1) provide a tutorial that is easy to follow for readers who are not already familiar with the subject, (2) make a comprehensive survey and comparisons of different methods, and (3) sketch a vision for future work that can help motivate and guide readers that are interested in texture synthesis research. We cover fundamental algorithms as well as extensions and applications of texture synthesis.
2009-01-01T00:00:00ZOver Two Decades of Integration-Based, Geometric Flow Visualization
https://diglib.eg.org:443/handle/10.2312/egst.20091062.073-092
Over Two Decades of Integration-Based, Geometric Flow Visualization
McLoughlin, Tony; Laramee, Robert S.; Peikert, Ronald; Post, Frits H.; Chen, Min
M. Pauly and G. Greiner
Flow visualization is a fascinating sub-branch of scientific visualization. With ever increasing computing power, it is possible to process ever more complex fluid simulations. However, a gap between data set sizes and our ability to visualize them remains. This is especially true for the field of flow visualization which deals with large, timedependent, multivariate simulation datasets. In this paper, geometry based flow visualization techniques form the focus of discussion. Geometric flow visualization methods place discrete objects in the vector field whose characteristics reflect the underlying properties of the flow. A great amount of progress has been made in this field over the last two decades. However, a number of challenges remain, including placement, speed of computation, and perception. In this survey, we review and classify geometric flow visualization literature according to the most important challenges when considering such a visualization, a central theme being the seeding object upon which they are based. This paper details our investigation into these techniques with discussions on their applicability and their relative merits and drawbacks. The result is an up-to-date overview of the current state-of-the-art that highlights both solved and unsolved problems in this rapidly evolving branch of research. It also serves as a concise introduction to the field of flow visualization research.
2009-01-01T00:00:00ZHigh Dynamic Range Imaging and Low Dynamic Range Expansion for Generating HDR Content
https://diglib.eg.org:443/handle/10.2312/egst.20091060.017-044
High Dynamic Range Imaging and Low Dynamic Range Expansion for Generating HDR Content
Banterle, Francesco; Debattista, Kurt; Artusi, Alessandro; Pattanaik, Sumanta; Myszkowski, Karol; Ledda, Patrick; Bloj, Marina; Chalmers, Alan
M. Pauly and G. Greiner
In the last few years, researchers in the field of High Dynamic Range (HDR) Imaging have focused on providing tools for expanding Low Dynamic Range (LDR) content for the generation of HDR images due to the growing popularity of HDR in applications, such as photography and rendering via Image-Based Lighting, and the imminent arrival of HDR displays to the consumer market. LDR content expansion is required due to the lack of fast and reliable consumer level HDR capture for still images and videos. Furthermore, LDR content expansion, will allow the re-use of legacy LDR stills, videos and LDR applications created, over the last century and more, to be widely available. The use of certain LDR expansion methods, those that are based on the inversion of tone mapping operators, has made it possible to create novel compression algorithms that tackle the problem of the size of HDR content storage, which remains one of the major obstacles to be overcome for the adoption of HDR. These methods are used in conjunction with traditional LDR compression methods and can evolve accordingly. The goal of this report is to provide a comprehensive overview on HDR Imaging, and an in depth review on these emerging topics.
2009-01-01T00:00:00Z