1 / 1

All-Frequency Precomputed Radiance Transfer for Glossy Objects interactive rendering of shadows, both sharp and soft, on

All-Frequency Precomputed Radiance Transfer for Glossy Objects interactive rendering of shadows, both sharp and soft, on non-diffuse objects. Xinguo Liu, MSRA Peter-Pike Sloan, DirectX Harry Shum, MSRA John Snyder MSR. all-frequency, diffuse lighting=6x32x32 env. map transfer=1x6144 matrix.

terena
Download Presentation

All-Frequency Precomputed Radiance Transfer for Glossy Objects interactive rendering of shadows, both sharp and soft, on

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. All-Frequency Precomputed Radiance Transfer for Glossy Objects interactive rendering of shadows, both sharp and soft, on non-diffuse objects Xinguo Liu, MSRA Peter-Pike Sloan, DirectX Harry Shum, MSRA John Snyder MSR all-frequency, diffuse lighting=6x32x32 env. map transfer=1x6144 matrix all-frequency, glossy lighting=6x32x32 env. map transfer=10x6144 matrix low-frequency, glossy lighting=5th order spherical harmonics (25 coefs) transfer=25x25 matrix PRT Formulation L = lighting coefficients Mp = transfer matrix (p = surface point) G(v) = view map (v = view vector) good accuracy with m=10 – 10D vector G(v) and 10 rows in matrix Mp uses BRDF factorization: original m=5, error=10% m=10, error=2.1% PRT Clustering/Compression divide lighting env. into 16x16 segments use Clustered Principal Component Analysis on 24 segments (each 2560D) like Vector Quantization but uses a linear subspace (16D) in each cluster lighting segment 1 lighting segment 2 lighting segment 3

More Related