Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th 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
A signal-processing framework for inverse rendering
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
The Radiometry of Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling the Space of Camera Response Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Radiometric Response Function from a Single Grayscale Image
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Ensuring Color Consistency across Multiple Cameras
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
Radiometric calibration from a single image
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
RGB calibration for color image analysis in machine vision
IEEE Transactions on Image Processing
Estimating Photometric Properties from Image Collections
Journal of Mathematical Imaging and Vision
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We address the problem of jointly estimating the scene illumination, the radiometric camera calibration and the reflectance properties of an object using a set of images from a community photo collection. The highly ill-posed nature of this problem is circumvented by using appropriate representations of illumination, an empirical model for the nonlinear function that relates image irradiance with intensity values and additional assumptions on the surface reflectance properties. Using a 3Dmodel recovered from an unstructured set of images, we estimate the coefficients that represent the illumination for each image using a frequency framework. For each image, we also compute the corresponding camera response function. Additionally, we calculate a simple model for the reflectance properties of the 3D model. A robust non-linear optimization is proposed exploiting the high sparsity present in the problem.