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The analysis-by-synthesis approach enabled the mapping of the 3D and 2D domains and a new representation of 3D shape and appearance. Their work is the first to introduce a statistical model for faces that enabled 3D reconstruction from 2D images and a parametric face space for controlled manipulation. [2]
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.
Although FaceGen generates conventional 3D mesh data, it uses a "parameterized" approach to defining the properties that make up a face, and by using a fixed set of parameters it is able to morph and modify a face model independently of output resolution.
3D model of a human face. Three-dimensional face recognition (3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition.
Generating and reconstructing 3D shapes from single or multi-view depth maps or silhouettes [1] 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.
A neural radiance field (NeRF) is a method based on deep learning for reconstructing a three-dimensional representation of a scene from two-dimensional images. The NeRF model enables downstream applications of novel view synthesis, scene geometry reconstruction, and obtaining the reflectance properties of the scene. Additional scene properties ...
The reconstruction of an image from the acquired data is an inverse problem. Often, it is not possible to exactly solve the inverse problem directly. In this case, a direct algorithm has to approximate the solution, which might cause visible reconstruction artifacts in the image. Iterative algorithms approach the correct solution using multiple ...
A single ray of light from x (3D point) is dispersed in the lens system of the cameras according to a point spread function. The recovery of the corresponding image point from measurements of the dispersed intensity function in the images gives errors.