On the relationship between radiance and irradiance: determining the illumination from images of a convex Lambertian object.

By Ravi Ramamoorthi, P. Hanrahan. Journal of The Optical Society of America A-optics Image Science and Vision, 2001

425 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Computer Graphics and Computer-Aided Design, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/2b2e21668e66111e30574d8b2af6d822388e3959

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In Atomic and Molecular Physics, and Optics

In Computer Graphics and Computer-Aided Design

In Environmental Engineering

Citations in the corpus

Lambertian reflectance and linear subspaces (2001, result): “(This part of our analysis was derived independently also by Ramamoorthi and Hanrahan [31].”
Exposing Digital Forgeries in Complex Lighting Environments (2007, background): “The key observation in [11] and [12] was that the coefficients for a Lambertian reflectance function decay rapidly and, thus, the infinite sum in (5) can be well approximated by the first nine terms”
Ieee Transactions on Pattern Analysis and Machine Intelligence 1 3d Face Reconstruction from a Single Image Using a Single Reference Face Shape (positive): “Under these assumptions it has been shown [2], [27] that Lambertian surfaces reflect only the low frequencies of lighting.”
Neural Face Editing with Intrinsic Image Disentangling (2017, methodology): “Therefore, we further assume distant illumination, L, that is represented by spherical harmonics [25] s.”
Plenoxels: Radiance Fields without Neural Networks (2021, background): “Spherical harmonics are a standard basis for functions over the sphere, and have been used previously to represent view dependence [4, 36, 47, 58, 59].”
Total variation models for variable lighting face recognition (2006, methodology): “The predominant ones include the Illumination Cone methods [6], [14], spherical harmonic-based representations [4], [29], [47], quotient image-based approaches [35], [34], [43], and the correlation filter-based method [32].”
A signal-processing framework for inverse rendering (2001, methodology): “For Lambertian objects, we [29] have shown how to recover the first 9 spherical harmonics.”
An efficient representation for irradiance environment maps (2001, background): “With these deﬁnitions one can show [16] that It will be convenient to deﬁne a new variable ˆ A l by For rendering, it will be convenient to expand out the irradiance.”
PlenOctrees for Real-time Rendering of Neural Radiance Fields (2021, methodology): “SHs have been a popular low-dimensional representation for spherical functions and have been used to model Lambertian surfaces [34, 2] or even glossy surfaces [44].”
Approximate Nearest Subspace Search with Applications to Pattern Recognition (2007, methodology): “In our experiments we used the YaleB face database [9], with images scaled down by a factor of 10. We ran leave-one-out tests, taking one out of the 65 illuminations as a query, and using the rest to produce a database with intrinsic dimension k = 9 (following [4, 18 ]).”
Face recognition under varying lighting conditions using self quotient image (2004, methodology): “Recent years, many algorithms have been proposed; let us highlight three major approaches of lighting modeling for 3D object recognition: as Illumination Cone [1]-[3], Quotient Image [4][5], and Spherical Harmonic Subspace [6-10].”