UC Davis

In this work, we introduced k-d darts as a particular type of higherdimensional sampling. We described a k-d dart framework for hyperplanes of general dimension k, and then demonstrated efficiency and accuracy over three applications using k = 1, and accuracy for one application using k = 1. In particular, darts produce accurate estimates of the volume of an object regardless of the dimension, orientation, and aspect ratio of the object. Axis-aligned darts are universally preferable to unaligned ones for sampling square domains, and we expect this to extend to hyperrectangles, such as bounding boxes. Darts also produce accurate mean estimates for function integration. © 2014 ACM 0730-0301/2014/01-ART3 15.00.