Model-based shape recovery from single images of general and unknown lighting

Authors:
Ham Rara;Shireen Elhabian;Thomas Starr;Aly Farag
Affiliations:
CVIP Laboratory, University of Louisville, KY;CVIP Laboratory, University of Louisville, KY;CVIP Laboratory, University of Louisville, KY;CVIP Laboratory, University of Louisville, KY
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 8
Cited 1

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Symmetric Shape-from-Shading Using Self-ratio Image

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Lambertian Reflectance and Linear Subspaces

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Active Appearance Models Revisited

International Journal of Computer Vision
Face Recognition from a Single Training Image under Arbitrary Unknown Lighting Using Spherical Harmonics

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering Facial Shape Using a Statistical Model of Surface Normal Direction

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Photometric Stereo with General, Unknown Lighting

International Journal of Computer Vision
Statistical approach to shape from shading: Reconstruction of three-dimensional face surfaces from single two-dimensional images

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Model-Based human teeth shape recovery from a single optical image with unknown illumination

MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging

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Abstract

We present a new statistical shape-from-shading framework for images of unknown illumination. The object (e.g., face) to be reconstructed is described by a parametric model. To deal with arbitrary illumination, the framework makes use of recent results that general lighting can be expressed using low-order spherical harmonics for convex Lambertian objects. The classical shape-from-shading equation is modified according to this framework. Results show accurate shape recovery with respect to ground truth data.