Abstract
We state that a one-dimensional manifold of shapes in 3-space can be modeled by a level set function. Finding a minimizer of an independent functional among all points on such a shape curve has interesting applications in computer vision. It is shown how to replace the commonly encountered practice of gradient projection by a projection onto the curve itself. The outcome is an algorithm for constrained optimization, which, as we demonstrate theoretically and numerically, provides some important benefits in stereo reconstruction of specular surfaces.
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Balzer, J., Höfer, S., Werling, S., Beyerer, J. (2010). Optimization on Shape Curves with Application to Specular Stereo. In: Goesele, M., Roth, S., Kuijper, A., Schiele, B., Schindler, K. (eds) Pattern Recognition. DAGM 2010. Lecture Notes in Computer Science, vol 6376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15986-2_5
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DOI: https://doi.org/10.1007/978-3-642-15986-2_5
Publisher Name: Springer, Berlin, Heidelberg
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