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IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 25th 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
Robot Vision
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Estimation of Multiple Directional Light Sources for Synthesis of Mixed Reality Images
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Multi-completion with Termination Tools (System Description)
IJCAR '08 Proceedings of the 4th international joint conference on Automated Reasoning
Recovering surface reflectance and multiple light locations and intensities from image data
Pattern Recognition Letters
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Estimating illumination parameters in real space with application to image relighting
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Evaluating the effect of diffuse light on photometric stereo reconstruction
Machine Vision and Applications
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Abstract--This paper presents the V2R algorithm, a novel method for multiple light source detection using a Lambertian sphere as a calibration object. The algorithm segments the image of the sphere into regions that are each illuminated by a single virtual light and subtracts the virtual lights of adjacent regions to estimate the light source vectors. The algorithm uses all pixels within a region to form a robust estimate of the corresponding virtual light. The circumstances under which the light source detection problem lacks a unique solution are discussed in detail and the way in which the V2R algorithm resolves the ambiguity is explained. The V2R algorithm includes novel procedures for identifying the critical lines that bound the regions, for estimating the light source vectors, and for identifying opposite light pairs. Experiments are performed on synthetic and real images and the performance of the V2R algorithm is compared to that of a recent algorithm from the literature. The experimental results demonstrate that the proposed algorithm is robust and that it gives substantially improved accuracy.