reflection mapping

(redirected from Environment map)

reflection mapping

A rendering method that simulates light reflecting on an object. It is a much faster method than ray tracing because it maps light over the image rather than actually computing the path the light takes. See ray tracing and radiosity. See also reflection.
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A group of researchers from the University of California San Diego and Google have found a way to relight photos "according to any provided environment map." The researchers have trained a neural network to take any photo and adjust its lighting at will - including direction, temperature, and quality of light.With this newly developed model, you can relight your portraits using various canonical or user-specified environments similar to the popular "filters" used by social media platforms like Instagram.
We store the network parameters and test in an experimental environment map. The test is designed as the following.
The basic principle is to use sensor information and odometer data with multifeature matching to build an environment map while determining the location of the robot in the map.
in [13] adopted the radio environment map to management the interference in cognitive radio networks.
To assist people in escaping from a hazardous (dangerous area) region quickly when an emergency occurs with guaranteed safety, while avoiding excessive congestions and unnecessary detours has been implemented using the environment map navigation.
Furthermore, in order to introduce additional details on the mesh, both the terrain and water are enriched with normal maps, and they use the environment map of the skybox to create some reflection as well.
The radio environment map, which was first proposed by Zhao et al.
NIST Operating Unit(s) ITL, ACMD Category Image Projection and Sampling Targeted Users Virtual Reality Developers Operating System(s) Linux Programming Language C++11 Inputs/Outputs Cube map images for input and single projected environment map images on output (or vice versa).
In our scheme, for saving memory, each particle carries a sample pose of robot individually and all particles share a common environment map.

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