When Is the Shape of a Scene Unique Given Its Light-Field: A Fundamental Theorem of 3D Vision?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Diffuse-Specular Separation and Depth Recovery from Image Sequences
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Multi-View Stereo Reconstruction of Dense Shape and Complex Appearance
International Journal of Computer Vision
Separating corneal reflections for illumination estimation
Neurocomputing
Multi-view stereo beyond lambert
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
3D surface reconstruction of a moving object in the presence of specular reflection
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
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The problem of accurate depth estimation using stereo in the presence of specular reflection is addressed. Specular reflection, a fundamental and ubiquitous reflection mechanism, is viewpoint dependent and can cause large intensity differences at corresponding points, resulting in significant depth errors. We analyze the physics of specular reflection and the geometry of stereopsis which led us to a relationship between stereo vergence, surface roughness, and the likelihood of a correct match. Given a lower bound on surface roughness, an optimal binocular stereo configuration can be determined which maximizes precision in depth estimation despite specular reflection. However, surface roughness is difficult to estimate in unstructured environments. Therefore, trinocular configurations, independent of surface roughness, are determined such that at each scene point visible to all sensors, at least one stereo pair can compute produce depth. We have developed a simple algorithm to reconstruct depth from the multiple stereo pairs.