Photometric method for determining surface orientation from multiple images

By Robert J. Woodham. 1980

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Citations in the corpus

3D Shape Induction from 2D Views of Multiple Objects (2016, background): “When the viewpoint is ﬁxed and the lighting is known, photometric stereo [32] can provide accurate geometry estimates for rigid and diffuse surfaces.”
Learning to reconstruct shape and spatially-varying reflectance from a single image (2018, unknown): “…subproblemsoftheinverserenderingproblem:e.g.,photometric stereomethodsthatreconstructshapeassumingknownreflectance andlighting[Woodham1980],andBRDFacquisitionmethodsthat reconstructmaterialreflectanceassumingknownshapeandlight-ing[Marschneretal.1999;Matusiketal.2003].”
Structured-light 3D surface imaging: a tutorial (2011, background): “Photometric stereo, pioneered by Woodham [13], is a variant approach to shape from shading.”
What is the space of camera response functions? (2003, methodology): “Examples of algorithms that explicitly use scene radiance measurements are color constancy [7, 13], construction of linear high dynamic range images [17, 4, 16], photometric stereo [2, 18, 20], shape from shading [12], estimation of reflectance and illumination from shape and brightness [14], recove”
The 4-Source Photometric Stereo Technique for Three-Dimensional Surfaces in the Presence of Highlights and Shadows (2003, methodology): “It was conceived by Woodham [19], [20], who first used it to recover local surface orientation.”
Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery (2010, background): “Photometric stereo [1, 2] estimates surface orientations from photographs taken from a fixed viewpoint under different lighting conditions.”
Ieee Transactions on Pattern Analysis and Machine Intelligence Shape, Illumination, and Reflectance from Shading (unknown): “Instances of this approach are photometric stereo [29], which use additional images with different illumination conditions to estimate shape, and in later work reflectance and illumination [30].”
Spacetime stereo: a unifying framework for depth from triangulation (2005, background): “Another common depth estimation technique is photometric stereo [30].”
Consolidation of unorganized point clouds for surface reconstruction (2009, background): “Aside from estimating point normals via purely geometric means, acquisition mechanisms such as photometric stereo [Woodham 1980; Nehab et al. 2005] are also possible but they are often subject to error caused by surface or illumination artifacts.”
Efficiently combining positions and normals for precise 3D geometry (2005, methodology): “For example, there exist technologies based on shape from shading or photometric stereo [Woodham 1980] that directly measure surface orientations.”
Real-Time Monocular Depth Estimation Using Synthetic Data with Domain Adaptation via Image Style Transfer (2018, methodology): “Conventional depth estimation methods have relied on numerous strategies such as stereo correspondence [67, 28], structure from motion [14, 9], depth from shading and light diffusion [73, 82, 1] and alike.”
Shape, albedo, and illumination from a single image of an unknown object (2012, background): “Instances of this approach are photometric stereo [30], structure from motion [12], and inverse global illumination [31].”