A New Computer Vision Technique can Recover 3D Info from 2D Images

A new technique in computer vision may enhance our 3D understanding of 2D images.

Currently, a new technique in computer vision may enhance our 3D understanding of 2D images. 3D models are a collection of points in 3D space, so they have a length, width, and depth. 2D images only have length and width components. It's been an important part of computer vision studies. Computer vision is a field of artificial intelligence enabling computers to derive information from images, videos, and other inputs. The problem is difficult for several reasons, one being that information is inevitably lost when a scene that takes place in 3D is reduced to a 2D representation.

3D understanding of 2D images:

There are some 3D modeling programs out there that can help you sculpt or create 3D models out of single 2D images. They do require a bit of time and patience. There is no software yet that can take a single two-dimensional image and produce a robust three-dimensional model. However, using a series of two-dimensional images and making a three-dimensional model through a process called photogrammetry. Photogrammetry is the art, science, and technology of obtaining reliable information about physical objects and the environment through processes of recording, measuring, and interpreting photographic images and patterns of recorded radiant electromagnetic energy and other phenomena.

There are some well-established strategies for recovering 3D information from multiple 2D images, but they each have some limitations. That is virtual correspondences (VCs). VCs are a pair of pixels from two images whose camera rays intersect in 3D. Similar to classic correspondences, VCs conform with epipolar geometry; unlike classic correspondences, VCs do not need to be co-visible across views.

Virtual correspondences offer a way to carry things further, that one photo is taken from the left side of a rabbit and another photo is taken from the right side. Researchers want to make computers that can understand the three-dimensional world just like humans do and they need to develop computers that can not only interpret still images but can also understand short video clips and eventually full-length movies.

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