Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Environment matting and compositing
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
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
A Theory of Multiplexed Illumination
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
ACM SIGGRAPH 2004 Papers
SIGGRAPH '04 ACM SIGGRAPH 2004 Sketches
Postproduction re-illumination of live action using interleaved lighting
SIGGRAPH '04 ACM SIGGRAPH 2004 Posters
Progressively-refined reflectance functions from natural illumination
EGSR'04 Proceedings of the Fifteenth Eurographics conference on Rendering Techniques
Animatable facial reflectance fields
EGSR'04 Proceedings of the Fifteenth Eurographics conference on Rendering Techniques
Adaptive sampling of reflectance fields
ACM Transactions on Graphics (TOG)
Tabletop Computed Lighting for Practical Digital Photography
IEEE Transactions on Visualization and Computer Graphics
ACM SIGGRAPH 2007 courses
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
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We present a simple method for relighting real objects viewed from a fixed camera position. Instead of setting up a calibrated measurement device, such as a light stage, we manually sweep a spotlight over the walls of a white room, illuminating the object indirectly. In contrast to previous methods, we use arbitrary and unknown angular distributions of incoming light. Neither the incident light nor the reflectance function need to be represented explicitly in our approach. The new method relies on images of a probe object, for instance a black snooker ball, placed near the target object. Pictures of the probe in a novel illumination are decomposed into a linear combination of measured images of the probe. Then, a linear combination of images of the target object with the same coefficients produces a synthetic image with the new illumination. We use a simple Bayesian approach to find the most plausible output image, given the picture of the probe and the statistics observed in the dataset of samples. Our results for a variety of novel illuminations, including synthetic lighting by relatively narrow light sources as well as natural illuminations, demonstrate that the new technique is a useful, low cost alternative to existing techniques for a broad range of objects and materials.