论文标题
使用部分增量分类和积累的快速几何修剪拟合
Fast geometric trim fitting using partial incremental sorting and accumulation
论文作者
论文摘要
我们提出了算法贡献，可提高在异常值影响的几何回归问题中鲁棒拟合的效率。该方法在很大程度上依赖于快速排序算法，我们提出了两个重要的见解。首先，部分排序足以进行x-TheThepile值的增量计算。其次，线性拟合问题中的正常方程可以通过在排序过程中跨x-the％边界上记录交换操作来逐渐更新。除了线性拟合问题外，我们还展示了如何将该技术另外应用于封闭形式的非线性能量最小化问题，从而在几何最佳目标下实现有效的修剪拟合。我们将方法应用于两种不同的摄像机切除算法，并展示了高效且可靠的几何修剪拟合。
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.
