Geometry Independent Surface Light Fields for Real Time Rendering of Precomputed Global Illumination

We present a framework for generating, compressing and rendering of Surface Light Field (SLF) data. Our method is based on radiance data generated using physically based rendering methods. Thus the SLF data is generated directly instead of re-sampling digital photographs. Our SLF representation decouples spatial resolution from geometric complexity. We achieve this by uniform sampling of spatial dimension of the SLF function. For compression, we use Clustered Principal Component Analysis (CPCA). The SLF matrix is first clustered to low frequency groups of points across all directions. Then we apply PCA to each cluster. The clustering ensures that the withincluster frequency of data is low, allowing for projection using a few principal components. Finally we reconstruct the CPCA encoded data using an efficient rendering algorithm. Our reconstruction technique ensures seamless reconstruction of discrete SLF data. We applied our rendering method for fast, high quality off-line rendering and real-time illumination of static scenes. The proposed framework is not limited to complexity of materials or light sources, enabling us to render high quality images describing the full global illumination in a scene.