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3D reconstruction from multiple images is the creation of three-dimensional models from a set of images. It is the reverse process of obtaining 2D images from 3D scenes. The essence of an image is a projection from a 3D scene onto a 2D plane, during which process the depth is lost.
2D to 3D video conversion (also called 2D to stereo 3D conversion and stereo conversion) is the process of transforming 2D ("flat") film to 3D form, which in almost all cases is stereo, so it is the process of creating imagery for each eye from one 2D image.
An example of monocular portrait images of human faces that have been converted to create a moving 3D photo using depth estimation via Machine Learning using TensorFlow.js [3] in the browser. With advances in machine learning and computer vision, [3] it is now also possible to recreate this effect using a single monocular image as an input. [4]
2D digital image acquisition is the information source of 3D reconstruction. Commonly used 3D reconstruction is based on two or more images, although it may employ only one image in some cases. There are various types of methods for image acquisition that depends on the occasions and purposes of the specific application.
3D projections use the primary qualities of an object's basic shape to create a map of points, that are then connected to one another to create a visual element. The result is a graphic that contains conceptual properties to interpret the figure or image as not actually flat (2D), but rather, as a solid object (3D) being viewed on a 2D display.
The product is called a 3D model, while someone who works with 3D models may be referred to as a 3D artist or a 3D modeler. A 3D model can also be displayed as a two-dimensional image through a process called 3D rendering or used in a computer simulation of physical phenomena. 3D models may be created automatically or manually.
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