See Iterative reconstruction for 3D reconstruction in Medical imaging.
In computer vision and computer graphics, 3D reconstruction is the process of capturing the shape and appearance of real objects. This process can be accomplished either by active or passive methods. If we allow the model to change its shape in time, we talk about non-rigid or spatio-temporal reconstruction.
These methods actively interfere with the reconstructed object, either mechanically or radiometrically. A simple example of a mechanical method would use a depth gauge to measure a distance to a rotating object put on a turntable. More applicable radiometric methods emit radiance towards the object and then measure its reflected part. Examples range from moving light sources, colored visible light, time-of-flight lasers to microwaves or ultrasound. See 3D scanning for more details.
Passive methods of 3D reconstruction do not interfere with the reconstructed object, they only use a sensor to measure the radiance reflected or emitted by the object's surface to infer its 3D structure. Typically, the sensor is an image sensor in a camera sensitive to visible light and the input to the method is a set of digital images (one, two or more) or video. In this case we talk about image-based reconstruction and the output is a 3D model.
- 3D modeling
- 3D data acquisition and object reconstruction
- 3D reconstruction from multiple images