Section: New Results

Multi view data processing

Participants : Rhaleb Zayer, Alejandro Galindo, Kun Liu.

Direct use of denoising and mesh reconstruction algorithms on point clouds originating from multi-view images is often oblivious to the reprojection error. This can be a severe limitation in applications which require accurate point tracking, e.g., metrology. we propose a method for improving the quality of such data without forfeiting the original matches. We formulate the problem as a robust smoothness cost function constrained by a bounded reprojection error. The arising optimization problem is addressed as a sequence of unconstrained optimization problems by virtue of the barrier method. Experimental results on synthetic and acquired data compare our approach to alternative techniques. This work has been presented this year at the 8th International Symposium on Visual Computing, [20] .

Figure 9. Example of denoising.