Shadow computation in dynamic scenes under complex illumination is a challenging problem. Methods based on precomputation provide accurate, real-time solutions, but are hard to extend to dynamic scenes. Specialized approaches for soft shadows can deal with dynamic objects but are not fast enough to handle more than one light source. In this paper, we present a technique for rendering dynamic objects under arbitrary environment illumination, which does not require any precomputation. The key ingredient is a fast, approximate technique for computing soft shadows, which achieves several hundred frames per second for a single light source. This allows for approximating environment illumination with a sparse collection of area light sources and yields real-time frame rates.

Global illumination dramatically improves realistic appearance\nof rendered scenes, but usually it is neglected in VR systems\ndue to its high costs. In this work we present an efficient \nglobal illumination solution specifically tailored for those CAVE\napplications, which require an immediate response for dynamic light\nchanges and allow for free motion of the observer, but involve scenes\nwith static geometry. As an application example we choose\nthe car interior modeling under free driving conditions.\nWe illuminate the car using dynamically changing High Dynamic Range \n(HDR) environment maps and use the Precomputed Radiance Transfer (PRT) \nmethod for the global illumination computation. We\nleverage the PRT method to handle scenes with non-trivial topology\nrepresented by complex meshes. Also, we propose a hybrid of\nPRT and final gathering approach for high-quality rendering\nof objects with complex Bi-directional Reflectance Distribution\nFunction (BRDF). We use\nthis method for predictive rendering of the navigation LCD panel\nbased on its measured BRDF. Since the global illumination \ncomputation leads to HDR images we propose a tone mapping\nalgorithm tailored specifically for the CAVE. We employ \nhead tracking to identify the observed screen region\nand derive for it proper luminance adaptation conditions, \nwhich are then used for tone mapping on all walls in the CAVE.\nWe distribute our global illumination and tone mapping computation\non all CPUs and GPUs available in the\nCAVE, which enables us to achieve interactive performance\neven for the costly final gathering approach.

Abstract We propose a fast, high quality tone mapping technique to display high contrast images on devices with limited dynamicrange of luminance values. The method is based on logarithmic compression of luminance values, imitatingthe human response to light. A bias power function is introduced to adaptively vary logarithmic bases, resultingin good preservation of details and contrast. To improve contrast in dark areas, changes to the gamma correctionprocedure are proposed. Our adaptive logarithmic mapping technique is capable of producing perceptually tunedimages with high dynamic content and works at interactive speed. We demonstrate a successful application of ourtone mapping technique with a high dynamic range video player enabling to adjust optimal viewing conditions forany kind of display while taking into account user preference concerning brightness, contrast compression, anddetail reproduction. Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Image Processing and Computer Vision]: Image Representation