Improved methods of estimating shape from shading using the light source coordinate system
Artificial Intelligence
Adaptive filter theory
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A signal-processing framework for inverse rendering
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
An efficient representation for irradiance environment maps
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
A Simple Strategy for Calibrating the Geometry of Light Sources
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Coupled Lighting Direction and Shape Estimation from Single Images
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Estimation of multiple directional light sources for synthesis of augmented reality images
Graphical Models - Special issue on Pacific graphics 2002
Multiple Light Source Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Transactions on Graphics (TOG)
Mixture of Spherical Distributions for Single-View Relighting
IEEE Transactions on Pattern Analysis and Machine Intelligence
A unified framework for scene illuminant estimation
Image and Vision Computing
Numerical methods for shape-from-shading: A new survey with benchmarks
Computer Vision and Image Understanding
Separating corneal reflections for illumination estimation
Neurocomputing
Estimation of multiple directional illuminants from a single image
Image and Vision Computing
Difference sphere: An approach to near light source estimation
Computer Vision and Image Understanding
LightShop: An Interactive Lighting System Incorporating the 2D Image Editing Paradigm
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Polygonal light source estimation
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Interactive rembrandt lighting design
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
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We present a new method for the detection and estimation of multiple illuminants, using one image of any object with known geometry and Lambertian reflectance. Our method obviates the need to modify the imaged scene by inserting calibration objects of any particular geometry, relying instead on partial knowledge of the geometry of the scene. Thus, the recovered multiple illuminants can be used both for image-based rendering and for shape reconstruction. We first develop our method for the case of a sphere with known size, illuminated by a set of directional light sources. In general, each point of such a sphere will be illuminated by a subset of these sources. We propose a novel, robust way to segment the surface into regions, with each region illuminated by a different set of sources. The regions are separated by boundaries consisting of critical points (points where one illuminant is perpendicular to the normal). Our region-based recursive least-squares method is impervious to noise and missing data and significantly outperforms a previous boundary-based method using spheres[21]. This robustness to missing data is crucial to extending the method to surfaces of arbitrary smooth geometry, other than spheres. We map the normals of the arbitrary shape onto a sphere, which we can then segment, even when only a subset of the normals is available on the scene. We demonstrate experimentally the accuracy of our method, both in detecting the number of light sources and in estimating their directions, by testing on images of a variety of synthetic and real objects.