A Lighting-Invariant Point Processor for Shading

Kathryn Heal, Jialiang Wang, Steven J. Gortler, Todd Zickler; The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 94-102


Under the conventional diffuse shading model with unknown directional lighting, the set of quadratic surface shapes that are consistent with the spatial derivatives of intensity at a single image point is a two-dimensional algebraic variety embedded in the five-dimensional space of quadratic shapes. We describe the geometry of this variety, and we introduce a concise feedforward model that computes an explicit, differentiable approximation of the variety from the intensity and its derivatives at any single image point. The result is a parallelizable processor that operates at each image point and produces a lighting-invariant descriptor of the continuous set of compatible surface shapes at the point. We describe two applications of this processor: two-shot uncalibrated photometric stereo and quadratic-surface shape from shading.

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author = {Heal, Kathryn and Wang, Jialiang and Gortler, Steven J. and Zickler, Todd},
title = {A Lighting-Invariant Point Processor for Shading},
booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}