  The 3D Gaussian splatting method has drawn a lot of attention, thanks to its
high performance in training and high quality of the rendered image. However,
it uses anisotropic Gaussian kernels to represent the scene. Although such
anisotropic kernels have advantages in representing the geometry, they lead to
difficulties in terms of computation, such as splitting or merging two kernels.
In this paper, we propose to use isotropic Gaussian kernels to avoid such
difficulties in the computation, leading to a higher performance method. The
experiments confirm that the proposed method is about {\bf 100X} faster without
losing the geometry representation accuracy. The proposed method can be applied
in a large range applications where the radiance field is needed, such as 3D
reconstruction, view synthesis, and dynamic object modeling.
