  We present an algorithmic contribution to improve the efficiency of robust
trim-fitting in outlier affected geometric regression problems. The method
heavily relies on the quick sort algorithm, and we present two important
insights. First, partial sorting is sufficient for the incremental calculation
of the x-th percentile value. Second, the normal equations in linear fitting
problems may be updated incrementally by logging swap operations across the
x-th percentile boundary during sorting. Besides linear fitting problems, we
demonstrate how the technique can be additionally applied to closed-form,
non-linear energy minimization problems, thus enabling efficient trim fitting
under geometrically optimal objectives. We apply our method to two distinct
camera resectioning algorithms, and demonstrate highly efficient and reliable,
geometric trim fitting.
