Update

3d_model.md

@@ -20,7 +20,7 @@ Let's now take a closer look at a basic classification of 3D models (we only men
     - **[implicit surfaces](implicit_surface.md), [signed distance function](sdf.md)**: Describe the model by a [distance](distance.md) function, i.e. function *f(x,y,z)* which for any point in space says the distance to the object's boundary, with this distance being negative inside the object. This has some nice advanced use cases.
     - **[heightmaps](heightmap.md)**: Typically used for modeling terrain, represent terrain height at each 2D coordinate, normally with a grayscale bitmap image. Advantages include simplicity of representation and the ability to edit the heightmap with image editing tools, among disadvantages are limited resolution of the heightmap and inability to represent e.g. overhangs.
     - ...
-  - **[point cloud](point_cloud.md)**: Captures only individual points, sometimes with additional attributes such as color of each point, something akin its size, orientation and so on. This is typically what we get as raw data from some 3D scanners (see [photogrammetry](photogrammetry.md)). The advantage of point clouds is simplicity, they can be relatively easily rendered (just by drawing points on the screen), disadvantage is that the model has no surface and volume, there are "holes" in it: point cloud therefore has to be very dense to really be useful and for that it can take a lot of storage space. Point clouds may be converted to a more desirable format with special algorithms.
+  - **[point cloud](point_cloud.md)**: Captures only individual points, sometimes with additional attributes such as color of each point, something akin to its size, orientation and so on. This is typically what we get as raw data from some 3D scanners (see [photogrammetry](photogrammetry.md)). The advantage of point clouds is simplicity, they can be relatively easily rendered (just by drawing points on the screen), disadvantage is that the model has no surface and volume, there are "holes" in it: point cloud therefore has to be very dense to really be useful and for that it can take a lot of storage space. Point clouds may be converted to a more desirable format with special algorithms.
   - **[wireframe](wireframe.md)**: Records only edges, again potentially with attributes like their color etc. Just as with point clouds wireframe model has no surface or volume, but it at least has some information about which points are interconnected. Nowadays wireframe is not so much used as a model representation but rather as one of viewing modes.
 - by **features**:
   - **UV mapped**: Having UV map, i.e. being ready to be textured.