Image-space Point Cloud Rendering
Paul Rosenthal, Lars Linsen · 2008
Point-based rendering approaches have gained a major interest in recent years, basically replacing global surface reconstruction with local surface estimations us- ing, for example, splats or implicit functions. Crucial to their performance in terms of rendering quality and speed is the representation of the local surface patches. We present a novel approach that goes back to the orig- inal ideas of Grossman and Dally to avoid any object- space operations and compute high-quality renderings by only applying image-space operations. Starting from a point cloud including normals, we render the lit point cloud to a texture with color, depth, and normal information. Subsequently, we apply several filter operations. In a first step, we use a mask to fill back- ground pixels with the color and normal of the adjacent pixel with smallest depth. The mask assures that only the desired pixels are filled. Similarly, in a second pass, we fill the pixels that display occluded surface parts. The resulting piecewise constant surface representation does not exhibit holes anymore and is smoothed by a standard smoothing filter in a third step. The same three steps can also be applied to the depth channel and the normal map such that a subsequent edge detection and curva- ture filtering leads to a texture that exhibits silhouettes and feature lines. Anti-aliasing along the silhouettes and feature lines can be obtained by blending the textures. When highlighting the silhouette and feature lines dur- ing blending, one obtains illustrative renderings of the 3D objects. The GPU implementation of our approach