Abstract
We consider the task of stereo-reconstruction under the following fairly broad assumptions. A single and continuously shaped object is captured by two uncalibrated cameras. It is assumed, that almost all surface points are binocular visible. We propose a statistical model which represents the surface as a triangular (hexagonal) mesh of pairs of corresponding points. We introduce an iterative scheme, which simultaneously finds an optimal mesh (with respect to a certain Bayes task) and a corresponding optimal fundamental matrix (in a maximum likelihood sense). Thus the surface is reconstructed up to a projective transform.
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Schlesinger, D., Flach, B., Shekhovtsov, A. (2004). A Higher Order MRF-Model for Stereo-Reconstruction. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28649-3_54
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DOI: https://doi.org/10.1007/978-3-540-28649-3_54
Publisher Name: Springer, Berlin, Heidelberg
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