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Gaussian splatting model of a collapsed building taken from drone footage. 3D Gaussian splatting is a technique used in the field of real-time radiance field rendering. [3] It enables the creation of high-quality real-time novel-view scenes by combining multiple photos or videos, addressing a significant challenge in the field.
Usage of Differentiable 3D Gaussian Splatting, that is unstructured and explicit, hence allowing for rapid rendering, and also can be projected to 2D splats. Intuitively the covariance of the gaussian's can be thought of as configurations of an ellipsoid, which can be mathematically broken down into a scaling matrix and a rotation matrix.
Gaussian splatting is a newer method that can outperform NeRF in render time and fidelity. Rather than representing the scene as a volumetric function, it uses a sparse cloud of 3D gaussians. First, a point cloud is generated (through structure from motion) and converted to gaussians of initial covariance, color, and opacity. The gaussians are ...
It is sometimes referred to as "4D Gaussian splatting"; however, this naming convention implies the use of 4D Gaussian primitives (parameterized by a 4×4 mean and a 4×4 covariance matrix). Most work in this area still employs 3D Gaussian primitives, applying temporal constraints as an extra parameter of optimization.
In scientific visualization and computer graphics, volume rendering is a set of techniques used to display a 2D projection of a 3D discretely sampled data set, typically a 3D scalar field. A typical 3D data set is a group of 2D slice images acquired by a CT , MRI , or MicroCT scanner .
Example of texture splatting, except an additional alphamap is applied. In computer graphics, texture splatting is a method for combining different textures.It works by applying an alphamap (also called a "weightmap" or a "splat map") to the higher levels, thereby revealing the layers underneath where the alphamap is partially or completely transparent.
2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
The Gaussian function has a 1/e 2 diameter (2w as used in the text) about 1.7 times the FWHM.. At a position z along the beam (measured from the focus), the spot size parameter w is given by a hyperbolic relation: [1] = + (), where [1] = is called the Rayleigh range as further discussed below, and is the refractive index of the medium.