Variational Shape and Reflectance Estimation

Neil Birkbeck, Dana Cobzas, Peter Sturm and Martin Jagersand,


Birkbeck, N., Cobzas, D., Sturm, P., Jagersand, M. Variational Shape and Reflectance Estimation under Changing Light and Viewpoints, European Conference on Computer Vision (ECCV) 2006, to appear

Birkbeck, N., Cobzas, D., Jagersand, M. Object centered stereo: displacement map estimation using texture and shading, Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT) 2006


Refinment of Neil's face

Refinment of a stone dog

Result with reflectance model
Lots of demos at Neil's page


Lots of results, demos and a detailed description in Neil's thesis

Mesh evolution to a refined shape. Left: Input image, Middle: evolution, Right: Result

Fitting parameterized 3D shape and general reflectance models to 2D image data is challenging due to the high dimensionality of the problem. The proposed method combines the capabilities of classical and photometric stereo, allowing for accurate reconstruction of both textured and non-textured surfaces. In particular, we present a variational method implemented as a PDE-driven surface evolution interleaved with reflectance estimation. The surface is represented on an adaptive mesh allowing topological change.

To provide the input data, we have designed a capture setup that simultaneously acquires both viewpoint and light variation while minimizing self-shadowing. Our capture method is feasible for real-world application as it requires a moderate amount of input data and processing time. In experiments, models of people and everyday objects were captured from a few dozen images taken with a consumer digital camera. The capture process recovers a photo-consistent model of spatially varying Lambertian and specular reflectance and a highly accurate geometry.

System overview diagram

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