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  2. UV mapping - Wikipedia

    en.wikipedia.org/wiki/UV_mapping

    UV mapping is the 3D modeling process of projecting a 3D model's surface to a 2D image for texture mapping. The letters "U" and "V" denote the axes of the 2D texture because "X", "Y", and "Z" are already used to denote the axes of the 3D object in model space, while "W" (in addition to XYZ) is used in calculating quaternion rotations, a common ...

  3. Parallax occlusion mapping - Wikipedia

    en.wikipedia.org/wiki/Parallax_occlusion_mapping

    Parallax occlusion mapping (POM) is an enhancement of the parallax mapping technique. Parallax occlusion mapping is used to procedurally create 3D definition in textured surfaces, using a displacement map (similar to a topography map) instead of through the generation of new geometry. [ 1 ]

  4. Parallax mapping - Wikipedia

    en.wikipedia.org/wiki/Parallax_mapping

    Relief mapping and parallax occlusion mapping are other common names for these techniques. Interval mapping improves on the usual binary search done in relief mapping by creating a line between known inside and outside points and choosing the next sample point by intersecting this line with a ray, rather than using the midpoint as in a ...

  5. Texture mapping - Wikipedia

    en.wikipedia.org/wiki/Texture_mapping

    Mapping a two-dimensional texture onto a 3D model 1: 3D model without textures 2: Same model with textures. Texture mapping [1] [2] [3] is a method for mapping a texture on a computer-generated graphic. "Texture" in this context can be high frequency detail, surface texture, or color.

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  7. Surface triangulation - Wikipedia

    en.wikipedia.org/wiki/Surface_triangulation

    This article describes the generation of a net of triangles. In literature there are contributions which deal with the optimization of a given net.

  8. Self-organizing map - Wikipedia

    en.wikipedia.org/wiki/Self-organizing_map

    Each node in the map space is associated with a "weight" vector, which is the position of the node in the input space. While nodes in the map space stay fixed, training consists in moving weight vectors toward the input data (reducing a distance metric such as Euclidean distance) without spoiling the topology induced from the map space. After ...

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