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
A comprehensive physical model for light reflection
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Measuring and modeling anisotropic reflection
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Can the Sun‘s Direction be Estimated from an Image Prior to the Computation of Object Shape?
Journal of Mathematical Imaging and Vision
Non-linear approximation of reflectance functions
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Object shape and reflectance modeling from observation
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Recovering photometric properties of architectural scenes from photographs
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Inverse global illumination: recovering reflectance models of real scenes from photographs
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Acquiring the reflectance field of a human face
Proceedings of the 27th 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
Multiple Illuminant Direction Detection with Application to Image Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Illuminant Direction and Intensity of Multiple Light Sources
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Estimation of Multiple Illuminants from a Single Image of Arbitrary Known Geometry
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Diffuse-Specular Separation and Depth Recovery from Image Sequences
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
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
Estimation of Diffuse and Specular Appearance
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Estimation of multiple directional light sources for synthesis of augmented reality images
Graphical Models - Special issue on Pacific graphics 2002
Interactive virtual relighting and remodeling of real scenes
EGWR'99 Proceedings of the 10th Eurographics conference on Rendering
Camera and light calibration from reflections on a sphere
Computer Vision and Image Understanding
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We present a new method for the detection and estimation of multiple directional illuminants, using only one single image of an object with known geometry. It 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. We first develop our method for the case of a Lambertian sphere with known size, illuminated by a set of directional light sources. A novel and robust way is proposed to segment the surface into regions, with each region illuminated by a different set of sources. Our region-based least-squares method is impervious to noise and missing data, which is crucial to extending the method to arbitrary smooth geometry and to surfaces having both Lambertian and specular properties. We propose a novel methodology that integrates information from shadows and shading in the presence of strong directional sources of illumination, even when significant non-directional sources exist in the scene and the object surface is not Lambertian. 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.