Improved Fast Gauss Transform and Efficient Kernel Density Estimation

  title={Improved Fast Gauss Transform and Efficient Kernel Density Estimation},
  author={Changjiang Yang and Ramani Duraiswami and Nail A. Gumerov and Larry S. Davis},
Evaluating sums of multivariate Gaussians is a common computational task in computer vision and pattern recognition, including in the general and powerful kernel density estimation technique. The quadratic computational complexity of the summation is a significant barrier to the scalability of this algorithm to practical applications. The fa st Gauss transform (FGT) has successfully accelerated the kernel density estimation to linear running time for lowdimensional problems. Unfortunately, the… CONTINUE READING

6 Figures & Tables



Citations per Year

457 Citations

Semantic Scholar estimates that this publication has 457 citations based on the available data.

See our FAQ for additional information.