Shadow volume

Abstract: In this paper we propose a novel method for detecting and removing shadows from a single image thereby obtaining a high-quality shadow-free image. With minimal user assistance, we first identify shadowed and lit areas on the same surface in the scene using an illumination-invariant distance measure. These areas are used to estimate the parameters of an affine shadow formation model. A novel pyramid-based restoration process is then applied to produce a shadow-free image, while avoiding loss of texture contrast and introduction of noise. Unlike previous approaches, we account for varying shadow intensity inside the shadowed region by processing it from the interior towards the boundaries. Finally, to ensure a seamless transition between the original and the recovered regions we apply image inpainting along a thin border. We demonstrate that our approach produces results that are in most cases superior in quality to those of previous shadow removal methods. We also show that it is possible to easily composite the extracted shadow onto a new background or modify its size and direction in the original image.

Abstract: In this paper, we present a new shadow mapping technique that improves upon the quality of perspective and uniform shadow maps. Our technique uses a perspective transform specified in light space which allows treating all lights as directional lights and does not change the direction of the light sources. This gives all the benefits of the perspective mapping but avoids the problems inherent in perspective shadow mapping like singularities in post-perspective space, missed shadow casters etc. Furthermore, we show that both uniform and perspective shadow maps distribute the perspective aliasing error that occurs in shadow mapping unequally over the available depth range. We therefore propose a transform that equalizes this error and gives equally pleasing results for near and far viewing distances. Our method is simple to implement, requires no scene analysis and is therefore as fast as uniform shadow mapping.

Abstract: This study presents a user-friendly image-sharing method for easier management of the shadow images. The sharing of images among several branches (distributed disks) using the proposed method has several characteristics: 1) fast transmission among branches; 2) fault tolerance; 3) a secure storage system; 4) reduced chance of pirating of high-quality images; and 5) most importantly, the provision to each branch manager an easy-to-manage environment (because each shadow image looks like a shrunken version of the original image). The current approach still has the small-size and channel-independent properties of our previous work, namely, the size of each shadow image is only 1/r of that of the original image, and any r shadow images can be used for restoration (the restored image is independent of which r shadow images are used).

Abstract: This paper presents a novel approach that uses graphics hardware to dynamically calculate a voxel-based representation of a scene. The voxelization is obtained on run-time in the order of milliseconds, even for complex and dynamic scenes containing more than 1,000,000 polygons. The voxelization is created and stored on the GPU avoiding unnecessary data transfer. The approach can handle both regular grids and locally optimized grids that better fit the scene geometry. The paper demonstrates applications to shadow calculation, refraction simultation and shadow volume culling/clamping.