The Iterative Closest Point algorithm is a widely used approach to aligning the geometry between two 3 dimensional objects. The capability of aligning two geometries in real time on low-cost hardware will enable the creation of new applications in Computer Vision and Graphics. The execution time of many modern approaches are dominated by either the k nearest neighbor search (kNN) or the point alignment phase. This work presents an accelerated alignment variant which utilizes parallelization on a Graphics Processing Unit (GPU) of multiple kNN approaches augmented with a novel Delaunay Traversal to achieve real time estimates.
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机译：迭代最近点算法是在两个3维对象之间对齐几何图形的一种广泛使用的方法。在低成本硬件上实时对齐两个几何的功能将能够在Computer Vision and Graphics中创建新的应用程序。许多现代方法的执行时间主要由k最近邻搜索（kNN）或点对齐阶段决定。这项工作提出了一种加速的对齐变体，该变体利用多个kNN方法的图形处理单元（GPU）上的并行化，并增强了新颖的Delaunay遍历，以实现实时估计。
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