ACM Transactions on Graphics (TOG)
Tricolor attenuation model for shadow detection
IEEE Transactions on Image Processing
A three-stage approach to shadow field estimation from partial boundary information
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Detecting ground shadows in outdoor consumer photographs
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Shadow removal in sole outdoor image
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Interactive shadow removal from a single image using hierarchical graph cut
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Estimating the Natural Illumination Conditions from a Single Outdoor Image
International Journal of Computer Vision
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This paper addresses the problem of shadow extraction from a single image of a complex natural scene. No simplifying assumption on the camera and the light source other than the Lambertian assumption is used. Our method is unique because it is capable of translating very rough user-supplied hints into the effective likelihood and prior functions for our Bayesian optimization. The likelihood function requires a decent estimation of the shadowless image, which is obtained by solving the associated Poisson equation. Our Bayesian framework allows for the optimal extraction of smooth shadows while preserving texture appearance under the extracted shadow. Thus our technique can be applied to shadow removal, producing some best results to date compared with the current state-of-the-art techniques using a single input image. We propose related applications in shadow compositing and image repair using our Bayesian technique.