atlas

Research map / 3D vision / Depth and stereo

Uncalibrated Photometric Stereo by Stepwise Optimization Using Principal Components of Isotropic BRDFs

CVPR 2016 · 3D vision › Depth and stereo · approach: Photometric stereo · 6 citations (OpenAlex)

Check your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Represent isotropic BRDFs with PCA bases and optimize basis coefficients, normals, and lighting stepwiseUncalibrated photometric stereo · MERL BRDFsMAE: 22.8° -> 4.03°Helped
Represent isotropic BRDFs with PCA bases and optimize basis coefficients and normalsCalibrated photometric stereo · MERL BRDFsMAE: 4.79° -> 1.32°Helped
Increase the number of PCA basis functions stepwise (ablation)Proposed method · Parametric BRDFsMAEHelped
Use too few normal clusters in normal grouping (ablation)Proposed method · Synthetic BRDF experimentsMAEHurt
Use more normal clusters for normal grouping (ablation)Proposed method · Synthetic BRDF experimentsMAEHelped
Group similar normals before optimization (ablation)Proposed method · Synthetic BRDF experimentsconvergenceHelped
Use randomized multipoint search during optimization (ablation)Proposed method · Uncalibrated photometric stereoconvergenceHelped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy