RT‐HDIST: Ray‐Tracing Core‐based Hausdorff Distance Computation

Abstract The Hausdorff distance is a fundamental metric with widespread applications across various fields. However, its computation remains computationally expensive, especially for large‐scale datasets. This work targets exact point‐to‐point Hausdorff distance on point sets. In this work, we present RT‐HDIST, the first Hausdorff distance algorithm accelerated by ray‐tracing cores (RT‐cores). By reformulating the Hausdorff distance problem as a series of nearest‐neighbor searches and introducing a novel quantized voxel‐index space, RT‐HDIST achieves significant reductions in computational overhead while maintaining exact results. Extensive benchmarks demonstrate up to a two‐order‐of‐magnitude speedup over prior state‐of‐the‐art methods, underscoring RT‐HDIST's potential for real‐time and large‐scale applications.